 The webinar will begin shortly. Please remain on the line. The webinar will begin shortly. Please remain on the line. The webinar will begin shortly. Please remain on the line. The broadcast is now starting. All attendees are in Listen Only mode. Hello and welcome to Enago's webinar titled How AI is Impacting Academic Publishing, Guide for Authors and Journal Editors. In collaboration with Trinker, an advanced artificial intelligence-powered writing assistant. This session will aim to help researchers understand how they can assess and enhance the quality of their thesis using an AI-powered language assistant tool. Before we begin, I would like to mention that you can send us your questions using the Questions tab in the control panel and our expert speakers would be happy to answer all your queries at the end of the webinar. Today, we have with us our expert speakers Dr. Stephen Huff and Mr. Rahul Kumar. Stephen is a published author with 20 plus years of experience in manifold scientific field including big data analytics, machine learning, algorithm development, laboratory management, and informatics research. After completing his PhD from the University of Houston, Dr. Huff continued his research pursuit as a research biological scientist at USAF Research Laboratory followed by his appointment at Noblesse, Inc. To date, Dr. Huff has published several research papers in high-ranking journals and is also a recipient of five grants and multiple awards and scholarships. As a publication and training consultant at the Nago Academy, Dr. Huff provides guidance to research scholars for a successful academic career. Rahul is a Bell-certified medical editor and an entrepreneurial product professional instrumental in developing Trinker. He has seven plus years of experience in academic publishing industry with expertise in editing, product development, and operations. He has conceptualized and built academia focused AI products for authors and publishers. We extend the warm welcome to our speakers and thank them for joining us today. Before I hand over the mic to Stephen, I would like to give you all a brief introduction about Nago. We are the world's leading author service provider and our author first quality first approach ensures that our authors receive only the best quality output and excellent user experience at all times. This unrelenting focus on author's needs means that we never compromise on our quality systems and processes at any cost. All our services are designed keeping in mind author's need. Nago Academy is a author training platform that educates authors through several resources including webinars as well as live workshop sessions. We also have an e-learning platform for researchers called Nago Learn along with live one-on-one consultation platform called Nago Consult. Nago offers world-class services to researchers at different stages of their research career such as two editor system English language editing service, academic and non-academic translation service, manuscript preparation service and publication support service. The Nago promise guarantees that a manuscript edited by us will never be rejected based on poor language. On their occasion if rejection occurs we will take full responsibility for re-editing the paper for resubmission at no additional cost. Nago's comprehensive after-sales services will support you at every step of the way until your manuscript is published. They are designed to take care of every need from the time you receive our main service until you are published. Nago's research communication service are designed to help you effectively present your research data. In case you are interested in any of these services feel free to email at webinars at enago.com. We also have exciting discount offers for our webinar participants details of which will be shared via chat box at the end of the session. Now without any further delay I will hand over the mic to Dr. Stephen. Good morning everyone. It's glorious day here. I hope the same is true for you. Today we're going to be talking about two or three things that are very near and dear to my heart. I'm sorry. Do you have a question? I would request you to switch on the presentation one. Working on that. We're going to be talking about two or three things that are very near and dear to my heart. Publication and artificial intelligence. Today we have four topics on the agenda. How AI is transforming the academic publishing landscape. How AI is assisting authors. How AI is assisting journal editors. A popular AI based tools to improve quality of publications. AI in the publishing landscape is many things related to artificial intelligence and they sit in business. It has an average growth rate on the publication side of articles anywhere between 5 and 6% per year. Typically these articles are being published in one of two classes of journals peer reviewed, non peer reviewed. But it is critical to ensure in either case, if you are the author in my opinion, that these articles are evaluated consistently and efficiently. So, previously, like many things that are being replaced this way, this was done manually by human beings. But artificial intelligence has many tools that can help here and we're starting to see these tools being utilized. So, the primary applications for these tools will be discussed in the presentation to follow. Essentially, they're aiding the publication higher quality manuscripts and they're doing that in a much more efficient way. At least that's the idea. Also, the tools are author as well because many of these tools can be used to increase the efficiency of your literature search and the internet to correlate and coordinate those articles together so that they make more sense without you having to do this manually, which is a tedious task that we've all done if we've written something like a dissertation or a thesis. And of course, you also have available databases that are also curated in some cases with AI that can aid your efforts as well. So, some novel applications of AI that are worthy of mentioning are a couple of different modes of operations. So, one classification of documents two, within those documents extraction of entities and then finally the enhancement of discoverability. So, the classification of documents is fairly straightforward in a manual sense and we simply read them all and then decide how you want to break down those categories whatever those classifications are and then you do that. When I wrote my dissertation many years ago, I did it electronically but I also had a very big binder with indexed tabs in it so that I could keep track of the articles according to whatever system that I needed to review them to refer them to as I was writing. One of the things that's really important when you're doing this of course is to be able to recognize within the documents what entities are interacting what are the subject matter as well, who's discussing what and not just from a person point of view or even from a point of view but within the context of the article, what's the focus to subject matter or the article that's being acted against it. Also, the advances in semantic search which I'm sure you're all familiar with by using tools like Google are really just, they've been impressive for a long time but when you apply them to the to a literature review, they're especially helpful because there's a wealth of knowledge out there and some of it's curated, some of it isn't so it's not to dismiss those non-curated items because these publications often require exorbitant fees to get them into the journal but at the same time, there is a difference of quality. The advances on the publishing side and semantic publishing are I think equally promising and that is the ability to put your article out there in a way that makes sure that the people that need it most get it. When you're talking about a plethora of journals out there, this can be a very challenging thing to do. These tools are designed to assist both authors and publishers obviously and I think that from my experience as a scientist and working with many scientists in the field, there's really two kinds if you're taking this perspective and the majority well, the minority of my colleagues don't like to write. They like to do the cool stuff that's working with the technology and the data coming up with the findings. They tend to write because they have to get public to get funding, to get these publications out that though a lot of this work by the way is done by research assistants for that reason and I find that in those cases, most of the time since they're not writers, they tend to not write so well and some of them don't write at all. They need a lot of help with this. The other very small portion of scientists enjoy that part of the business probably more than anything else and it reflects in their work. If you're lucky and you're working on a collaborative team, you have a human being that's in that minority group and they take over the editing for you, but if you like many of my colleagues don't, these tools can provide great benefits. So they can, for example, look into your article and identify different kinds of errors and shortcomings that do it a lot faster than a human being can. And the kinds of errors and shortcomings that they can identify is to assist the language quality, for example, a high quality scientific text in my opinion. Again, it is just my opinion, but I think it's a fairly well reflected opinion, is that it's written in the first person active voice. So you say we did this, not this was done. And it takes credit for the work that you're doing, but it also makes sure that you're signing the active labels to the work that you're doing. When you use the passive voice, it sort of implies that anybody could have done the work. So also it can be used to evaluate the integrity of the figures. There are, of course, direct incidents of plagiarism, very well known in the scientific history, but these things also happen accidentally. And one of the things I've seen quite often is the use of figures. And sometimes because you've got so many of them and you're sorting through them, you might put the same figure in the same place, intending to replace it maybe later or just by accident selection. So it's very easy to spot that with these tools. Other times, if you're the publishing side and you're concerned that you're getting low quality perhaps plagiarized content, it helps to screen it on that way as well. And it can also, for those reasons, help identify predatory publishers. And I've been victimized by these. If you go look at my dissertation online right now you'll find that it's written by somebody else. But of course what it is is somebody that's taken my dissertation link somewhere and wrapped it in their text online and put their name on it. So if they come up in the search windows when somebody is searching for the subject matter of my dissertation. There's not a lot I can do about it, but of course if you're a publisher you have legal staff that could probably assist you with these things. So it's important that you be able to find these items and it's really obviously unreasonable to expect that anybody's going to search through the entire internet on a daily basis to do this. So I think that's a couple of really big benefits for both authors and publishers. So sort of maybe not ranking them in your priority, but in some sort of order. These tools help you to reveal trends and patterns for essential research, which is really essential in it. That's all the fundamental first step of the literature review is screening a huge volume of information about publications of various kinds, presentations, potentially PDFs, documents almost all that online now. And then putting into some sort of order. On the publishing side and essentially for your side of the author and some journals allow you to suggest reviewers you can identify reviewers that maybe you weren't able to find and this is a very challenging thing to do because most scientists tend to focus very, their work very narrowly, which means there's not a lot of them out there. So if you're working in a very esoteric space you might have a handful of potential reviewers and of those if you might have time. Plagiarism is a big issue not just from the author's perspective self-managing their own publications but from the idea that this is my intellectual property. I want to make sure that if somebody's using it outside the domain of my work that they're referencing and using it properly or compensating me somehow. Identification of funding sources is huge there's more and more of these every year and of course there's a lot of them that have been traditionally funding that are no longer viable. So you want to keep that list fresh. This is a tedious thing. I had a bunch of students sometimes that was one of their minimal task assignments was to periodically go out and do this for us. Being able to do it electronically saves time for my research assistant puts them back in the field doing what they like to do better. And also of course identified flawed reporting and statistics and data fabrication. That's both on your side and their side. The worst thing you can do I think the worst mistake you can make as a scientist from a publication point of view is send out a faulty script. We circulate that among our collaborators among all the contributors repeatedly to try to get that right but mistakes where all human and mistakes do happen. So there's like I said two perspectives for this discussion. The perspective of the author and the publication. The publisher and the author really has kind of two sub-perspectives because one is I'm writing and the other is I'm researching so it helps in both those fields as well. So journal selection how are you going to you know as a poor student at public schools my first objective when I was doing literature review was to find one where I could get the full text. So used to be we would go to a thing called the library which had these amazing things which were called books and you could actually pull them off the shelf read through these condensed collections of journal articles and then if they were on micro fish maybe even in the old school way you could take them down to the library and copy them for you. So you could get copies of the journal articles that way. Nowadays it's all online obviously but I still want the full text journal not just the citations or the abstract. So just that one filter can be of a huge benefit and obviously you want to match it for your subject matter interest and then within that perhaps sub-categories because most scientific concerns have multiple perspectives right so I might be working on a problem in my domain but other domains, sociology, psychology, physics, mathematics have influenced and have interest in that domain. I want to bring articles from all those perspectives. So I also want to make sure that I know that this is a mathematically oriented paper this is a paper that's oriented to the social sciences perhaps and then within that sub-categories and on and on. So the reason why you want to do this obviously is to improve the quality of your manuscript to reduce the odds of rejection. Save you time but in my experience save the time of your colleagues and contributors, your research assistants if you're running a lab, all of that equals money. So obviously you can also use this to locate articles not just for your interest as a researcher but as an author. I want to find, I want to get my article into the most prestigious and specifically focused journal that I can. So the case in point at the bottom is very relevant and what Bear is mentioning here that not all journals are a good fit for your article and doing a careful screening that's going to save you a lot of embarrassment perhaps in the long run because ideally you would like to be published in a peer reviewed journal those typically require that you take quite a bit of money I mean relatively speaking we're talking about poor scientists here and so it's very critical of that reason alone to get it right but to be able to tailor your publication to its audience a lot of times as a graduate student my targets were non-curated journals or things like conferences because I just wanted to put in a look with paper or a description of a couple of my graphics and findings just to get them out there not necessarily a full-blown publication there's all kinds of layers to this kind of investigation. So finally you've decided where you want to publish some of your research now you want to start writing and this is also a very tedious thing for most of us even for somebody like myself who likes to write I like to do the creative side of writing the part where I've got to manage margins and templates not so much fun. I personally used a thing called LaTeX when I wrote my dissertation was a huge help I could plug the analytical language that I was writing in directly into LaTeX and the text was beautifully formatted very very subtle changes very quickly but I had to have a lot of expertise to do this so it took a long time I won't say a long time but there was a learning curve learning LaTeX because it is a very dense application. So once you've decided how you're going to where you're going to publish you have to get their template their specifications and then start trying to match your output to their guidelines. These guidelines include different kinds of specifications from the journal that's sort of formatting issues with the kinds of things that you do to tables and images there's editorial guidelines some of them can be very specific especially those very prestigious journals they don't mean to stupid about to accept your work you will sort of stupid about to get them to accept your work so there's also a lot of rigorous detail in most submission procedures again it's scaled according to let's say the quality of the journal so those with higher quality will have higher standards when I say higher quality what I mean specifically is a wider dissemination to a discerning audience that is more accepting of the standards of that journal simply because it has that tradition all the way down to the micro journals that are basically publish yourself you just stick it in there and there's really no curation whatsoever. Also there's copyright and ethical guidelines again that such as on both intentional and accidental plagiarization and use of non-license images which is a big problem I know this is a big problem especially for graduate students they just pull it off the internet stick it in there presentations and put it up there without ever mentioning or listing on their slide that they borrowed it. In most cases this is not a violation strictly speaking if you're using it this way as long as you are putting somewhere on there that you did not create that that you took it somewhere with an academic license it still has to be referenced properly and then artificial intelligence is also a system of preparation of the draft of the scientific manuscript and this is what I like the best right for those that big say according to zip's law say 80% don't and 20% do like the right for that 80% and the 20% you know it's nice to have a little double check if you really get at it but for the 80% that really hate writing and there's a spectrum those that they really hate it and those that will tolerate it really don't mind it and then within that spectrum there's a lot of things that artificial intelligence nowadays can do especially natural language natural language natural language processing tools that can help us significantly not only formatting the text as far as physical layout but doing things like assessing language first person versus other voices and active versus passive very simple for spotting correct even and then based on experimental data software can also provide a structured draft for those authors to edit and develop further if you really want to just so I think there's kind of two schools of thoughts here is I want to create the initial draft and then have something help me clean it up right I like that up front control but I don't like the messy part on the back end the other school of thought is man I really don't like putting it I don't mind doing the edited on the back end but I don't like putting together so there's tools that you can use to do a real basic rough draft that's actually quite good these days and then all you do is read it for language in particular details is sort of sort of seeing what your work so there's you know levels of accommodation I'm sure levels of capability levels of cost of assuming as well if you're somebody like me you can potentially write these tools very quickly by the way something like AWS using their services it's also almost free scope of very small projects so if you have those skills you can do it yourself and then maybe create a product and become the next big guy it's a wide open field the tools are still in development so the second thing that we second aspect of this discussion as far as enhancing your writing quality as an author is that there are a growing number of tools that can actually provide certain stylistic accompaniments to your writing so we have these things called autoencoders generative models where I can take a photograph and run it through these things and suddenly it looks like Rembrandt painted it which is really cool but the equivalent in the literary domain is also available so the grammar checkers are not what they used to be they you know I started writing many many years ago back before I actually started writing on a typewriter you must know and then we had these specialized things called word processors and now we call them office suite tools but the grammar checkers have been getting better and better over the years but the tools that they're using now are not simple rule based algorithms these things are actually incorporating these new artificial intelligence tools and they're much more effective so they can do a lot more identification of problem space for you but they can also do a lot more correction fees of course I still have trouble splitting out there there and there right with the EIR and the ERE and the EY possibly RE still some spots where it's not going to be perfect but for you, for those of you that don't like the right that don't feel confident in it because you don't do it a lot it could be a big boom it could just be this confidence check when you send out your manuscript that said you know I did the best I could do because sometimes that's all that you can do when it comes to the use of language grammar or use of punctuation I mean what is the subject of the verb and etc most of us don't spend a lot of time in that realm so you can use these tools to triage the paper as already indicated edit the language identify all the irregularities that we've already discussed you can also use it to screen missing information ethic statements patients etc because basically these tools are really good at you know these NLP tools are really good at a couple of different things one of them is looking at the big picture formatting if you're supposed to have the author's list and then their associated academic or whatever professional institutions list and you switch that around you can see those kinds of things easy missing missing components are also very easily identified these are the kinds of things you don't see for looking at the forest you can't see the trees sort of issues so it's very again if nothing else it can provide an excellent confidence check at the end of the publication process and of course these things are being more and more capable so the idea that they can identify within the document that's the smart sort of take it from the macro to the micro picture problems with things like your ethics statements patient consent your methods you've been inconsistently using terminologies you know chemicals often have multiple names especially very familiar chemicals I like to be consistent when I'm writing if it's a certain kind of chemical I like to call it that name throughout not by its various different names because it's confusing you know it's an easy mistake to make because a lot of times we write these papers and phases so months maybe years apart we might change our language over time so also the accepted cases of academic fraud especially involving things like data and images are very easily identified with these tools I actually had a personal experience with one colleague using images of another colleague became a big brouhaha I won't comment whether it was ethical concerns involved but it ultimately boiled down to the two of them had a very closely related file systems that had very similar names they were stored without security so one could see the other and it could have been a potential case of confusion so whether it's intentional or not intentional that things happen so how does AI help the journals publishers and you may be wondering why do I care about this if you're not a publisher most publishers deal with authors so they understand that side of the discussion but authors may be not understanding why do I need to think about what a publisher goes through well those are your that's your target audience if I'm writing a proposal to a particular scientific entity they have you know funding entity they have their focus I want to write to that focus or I know it's wasting my time so I also as a as a scientist within a collaborative group become a publisher for one thing if I'm working with my graduate research assistants our fellows I'm usually the the guy that reviews all their work before it goes out to the the collaborators that they're working with that's coming out of my lab so in a sense I am a publisher so what can these tools do to help us here they can reduce the time of a publication obviously by streamlining the most basic reviews you know do you have your author's list in the right place those kinds of things I can enhance the author experience if you find the task the manual task of authorship tedious then the software may be automated to the point where you actually begin to enjoy it you focus on the parts that you like and you don't have to do the parts you don't like so much it can obviously improve editorial quality for a lot of different reasons based on you know the semantics and systematic or syntax of the document as well as things like plagiarizations we already talked about which means that you can get the publication to market faster as a both an author and a publisher you can get better budget predictability because human problems tend to be messy and fuzzy and non-definite whereas the performance of an algorithm is fairly deterministic so if I put a document of a certain size and I run a thousand of those I get I know about how long it's going to take to analyze that it's not going to vary because they've had a bad day or they wrecked their car or you know where they're sitting also it reduced for obvious reasons overall costs from acquisition to publishing it can produce improve the publishers in-house staff productivity because again you know even though you are a publisher and you have editors on your staff there's things that people like to do and don't like to do in their job and they can use the tools to sort of balance that a little bit so that they're much more engaged and much more interested in what they're doing because they could spend more time doing what they like doing what they don't like and of course to boost the immediacy of science because all of these things come together to make a much more efficient scientific market place so peer review what is peer review just to be clear this is the process where you take a scientific publication and you pass it around to experts and this is important non-experts that's the part a lot of people forget the experts are going to look at and check the technical quality of your work hey you know I don't agree with your theory necessarily but I do like the way that you've done this except for this one step seems a little questionable and if you could resolve that I feel a lot better about your overall theory too but of course there's also the problem of of establishing who's going to do that peer review process and what their guidelines are so think of these artificial intelligence tools as your peer reviewer right and the nice thing about that is it's going to be objective both of the technical and non-technical audience because like I said the thing that a lot of us forget is to take that article and put it in front of somebody that's not in the field so you don't want to put it in front of a fifth grader probably if you're doing high level science before unless it's a very intelligent fifth grader I've met some of those but you might want to put it in front of a scientist in a different field an engineer I've always enjoyed having engineers read my work because they're very meticulous about the equations and the data points and then of course somebody even a literary feel would be good too right just review it for the quality of the language let me switch voices your active passive active passive right so it can be used to evaluate the manuscript it can be used for mechanical things like extracting key terms for originality and relationship mapping by the way if you've ever had to parse out your non-manuscript or a manuscript of any kind for key words is that fun I mean every single in a scientific manuscript you want to say all of these are key words right except for the fundamental language in it so but the question is what are the key words that are going to bring the right audience to your text and to your journal if you're publishing and so check for language quality issues identification of plagiarism optimizing editorial workflows and we'll talk about one of those here at the end of the discussion match papers to journals and reviewers which I said like I said it's not always an easy thing to do not just because there's a few of them out there but because you to take the time to be a peer reviewer if you're not a collaborator and they're not getting paid they do this for to stay current you mean that's why I typically do it I get a little I get a little cheese at the end when they put my name as a reviewer but I do it typically to stay current in my field see what the fellows of other guys doing I can also use the collab collaborate calibrate reviewer scores to reduce bias if we're working in the data science business we know about normalization and sometimes very compelling to look at something that's a big huge difference is a wow that's phenomenally impressive but when you normalize it the difference disappears so it's important to take that human subjective quality score and somehow equate it to one another and they can check for partly described methods and value confusion missing data components in this template so to wrap up illustration here just to sort of put it all together in a single point AI tool and peer review this is the work for the workflow that I was that I mentioned previously this is called I'm not sure exactly how they pronounce this but I will call it as I'm going to assume they mean it kind of like advice but it's created by else else else of I sometimes can say it sometimes and it's basically built to replace their outdated editorial system and support the editorial process that they have to undertake for their publications and speed up the whole overall process so some of these things obviously well all of these things once upon a time we're all done manually so before the internet if you were sent to have publication into a journal and this is why before the internet there were a lot fewer of them you absolutely if you were staking the claim that you are peer-reviewed your publication you absolutely had to have somebody that much like they do in the patent office take the article and then go out and research current publications in the literature from other journals other authors to make sure that you're not repeating something and if you see you know a big picture oh this article and this article sound a lot put it together then they had to go text by text highlight the parts that you know are actually word-for-word copied or whatever the images very tedious software can do this quite readily and very quickly it's been around plagiarism the checkers have been around for a long time I wrote one 20 years ago for a class that I a little coursework that I was teaching and all it did was take their article bust out the big words and then just do an internet search and then find the top rated documents and then just compare them together how much how much are they alike as you go through them and just give a score they're much more and I wrote that in a couple of days in ASP.net for a web browser but they're obviously a lot more capable than that these days so when we talk about plagiarism checking software we're talking about something that can be very substantial beware by the way so automatically to prepare things like the correspondence among the parties involved I don't know exactly how they've implemented this but I've also done this many times essentially you're talking about a workflow something like SharePoint for example if you're a Microsoft user can be done can be used to do this so you just have checkpoints along the workflow once this person gets done signs off on it sends out that burst of emails or writes those number of letters and then moves it to the next person in the line so my that's important is obviously people take vacations back in the old days papers get dropped they fall behind desks you know things don't get moved from one outbox to another inbox so this happens electronically as well these automated workflows simply ensure those checkpoints along the way or check and then the tedious stuff is done the worst thing you can do is send out a thank you letter to an author and put somebody else's name in the author's slide or misspell their name so if you've got it in this in your database I'm assuming correctly and you've got the author to approve all that point from that point forward and use that same name it's been vouchsafed and you know that it's at least as right as anybody said it was and nobody complained so far but if you're hand in hand to hand key this or copy and paste doing these tedious operations in the current era of a very significant nature so I can do things like send decision letters to the authors I would imagine that from my perspective in data science that these decision letters can be automated to a greater or lesser degree the decision may be completely automated I reviewed your paper for all these things that we talked about and without even looking at it I can say I don't it's not in my field or the quality isn't good enough you can probably do a lot of rejections up front and then sort of spend your time on the on the acceptances that you really want to focus on you can also use these things like invite alternate reviewers and I'm assuming again the database is probably quite extensive it has passed and potential reviewers in it so that somebody that has done work in the past is currently signed up paper can quickly be called upon to fill that gap and again this is this thing this is something that can be overstated because this is a negotiation process right but if you already have them in your system and you've already done that negotiation process and you can use these systems to rapidly and automatically identify and assign those tasks man that's that's just a huge it's a big thing it's a big boost for the reviewer as well because it can be very tedious to have to go oh god I got to answer another email I'm in the middle of publishing here myself right I can also do things like send thank you letters to reviewers and man you're gonna say oh that's a very trivial thing let's just forget that in the manual process those are the kinds of things at the end of the process that you say look we just don't we're starting a whole new thing we don't have time let's just skip that part well that's the part that really gets you you know brings back repeat reviewers repeat authors repeat business of various times and it also imbeers you to them when you talk about women hearts and minds and I really like that journal you know they they took care of me from the beginning and then never forgot I communicate with other programs to check things like the profile scientific performance conflicts of interest of yours it added an item but I would think the big thing here would be what they call SEO I don't know what they call it more recently but search engine optimization right because these things are typically going to get published in a paper journal if you're on buy-in so-called but they're most often also going to end up online typically in the paid journals as abstracts and citations only so you've got to have very expensive by the way these things can cost tens of thousands of dollars per per per seed access just to get access to something like Elsevier can be quite prohibitive from a capital point of view and so managing these things can be very critical. Finally you can do things like provide reminders to your reviewers I myself have been subjected to these reminders I have 20 or 30 applications for a prestigious fellowship that I have to review by Saturday for example I mean I have my own reminders in my calendar and keep doing that until it's done but obviously things get left by the wayside and if you've got a 30-day deadline and it's 21 days into that you really would like to know if I'm going to get this from you in the next nine days because I can go back to the other AeroPoint here and get an alternate review if you've suddenly become being incapacitated or too busy and of course suggestion of review is also very helpful so I've talked to quite a bit quite a few aspects of AI tools that are used today to help improve the quality of both your authorship and your publication stream do you have any questions I hope you'll ask them thank you I think we will go through these slides about the tools that we have to offer for authors specifically which would help the authors really get published faster. Like Dr. Stephen was explaining we have three tools to explain take you through one is Trinka which is focusing on the language quality part which is writing assistance and author 1.ai which is focused on helping you understand the manuscript's readiness for general submission and open access journal finder which will help you identify the right journal for your paper so let's dive into Trinka first Trinka is the only AI writing assistant that makes academic and formal writing easy and it's custom built for academic writing like other tools in the market like Grammarly or maybe a Perfected or a Ginger Trinka has been specifically trained on academic content about 1.3 million papers from different genres which makes it unique and basically it gives it the ability to understand the academic nuances within the academic writing just to give you a brief background Trinka comes from the house of Inago so we have about 15 years of experience having worked with authors globally and publishers as well and that also obviously goes into how we have built Trinka and the expertise that we have to really rely on so in terms of improvements that Trinka can offer, Trinka can obviously improve the tone the grammar, the spellings of course but apart from that we have also built in unique features which help in reducing your word count so that you can meet the journal guidelines which are stringent sometimes that then structure and bias language and then technical phrasing and vague language usage now these obviously go towards making your manuscript a little more polished giving it a more formal appeal and finally our spelling system is again advanced it understands the contextual differences between let's say a from and a from in general text and also between such words, confusing words which sound similar but then they are spelled differently even in academic context and finally Trinka also has unique features that help in journal submission towards preparing a mask towards your submission for example Trinka is capable of offering you subject area based collections which would mean that if you are writing a paper in cardiology you can tell Trinka that you are writing a paper in cardiology the suggestions that you will receive will be in tune with the subject you will also offer a consistency check similar to most tools in the market again with a bent towards academic writing which help you achieve the consistency that you need for a final submission and for authors to save time to save their time we have a unique feature called Trinka in the market which lets you upload a word document and receive all the edits in one shot in the document itself in track changes and finally the publication checks help you understand your manuscript's readiness across from different checkpoints which I will demonstrate to you in the slides in the Trinka product and in fact indeed so what I am going to show you right now is a quick look at the Trinka writing platform this is the marketing website you will have to go to understand what Trinka offers that's trinka.ai you can register for free or log in once you do log in you will be taken to your my drive where you can upload a file once you do upload a file the file becomes available for you to really go through all the errors that the AI system is suggesting like I mentioned Trinka is specifically trained for academic content about 1.3 million documents of different subject that gives it the edge that it really needs to work best with the academic content the experience is very simple all you need to do is just go through the underlined words which indicate a possible error and make the corrections by clicking the correction suggested on the right hand side you will also see that there would be explanations given to you for the change so you understand why the change is necessary and at times you will also see multiple options from the AI system the changes can obviously be from just being grammar and spelling corrections to those two words making your text concise or maybe more formal sounding or even to basically adhere to a style guide we have style guides built into Trinka so if your journal prefers a particular style guide you can choose for the American Medical Association or American Psychological Association etc and that is automatically applied to your document which makes the entire compliance to journal guidelines very easy and finally you can also customize your writing type if it's academic writing you can tell Trinka that you are writing an original article or a case report or even choose from the automatically detected subjects for your paper once you've done that you will see suggestions coming to you in a more customized fashion similarly we have the consistency checks which will analyze the entire document to maintain consistencies like use of different number formats between spelled out numeral or number indigits or spelling variations between British and American which can be taken care of in one simple click so that's how Trinka can actually make writing a lot more easier and then polishing your manuscript before the submission a lot more easier these are some examples of different subject areas we have that Trinka can work with and a few examples of how it really adds value to your language Trinka is also available as an MS word add-in within the word application on windows and you can also use Trinka on the Chrome browser as an extension or the Firefox browser as an extension and on edge as well and of course Trinka is available on the web as trinka.ai now let's talk about author one manuscript evaluation system that basically incorporates the ethical and different technical checks which Dr. Stephen was talking about in the earlier slides the system can perform over 60 different checks using AI technology to give you a quick assessment of where your manuscript really stands as far as generic requirements for publication are concerned. You will get a report which indicates a lot of readiness score as well so it's easy for you to understand the effort involved in making it ready. The product uses AI technology and of course the editorial intelligence we have gathered over years and why working with publishers as well and this is a quick look at the different kind of checks you will see on the author one platform of course there is a writing quality check and then after that you will also be able to see how well your manuscript matches the scope of the journal that you are targeting then the keywords that you can use to make it more visible after it's published so you get more views on your research and similarly it can generate a summary for your manuscript so you can share it across social media or any other platform that you would want your paper to get visibility on and plagiarism check as well. We use authenticates which is a gold standard plagiarism check that you will get on the author one platform and finally we have the other technical and ethical checks as well which I will show you in a quick demonstration right after. Let's take a look at the author one platform once you log in which is through author one dot ai you will be greeted to this dashboard where you can see all the reports that you have processed and also upload a new one. You can choose between the basic and which is free offering and the premium offering which obviously gives you the full report with all the checks that the system can do and also the plagiarism check as well. Once you have processed the files you will see the links for the report of course and I have opened a report for you to take you through quickly. The report will be sectioned on the left hand side with different sections that are you know the checks are categorized into. You will see the title of the paper that has been fixed automatically along with the word count the figures and tables in it and the author names and whether the author correspondence email has been present. You will see the overall description of whether your paper meets the requirements for publication requirements or whether it needs change and a quick summary of the entire the four major checks we do including language scope match for the journal target and plagiarism check and finally ethical compliance with a numerical scope. As you go further you will see in detail all the sections where the AI system has generated the report for you to understand your manuscript readiness. Starting with the summary which you can use to quickly gather the sentences which are the highlight for your paper. Then with concepts which can be used also as keywords based on the concepts and the summary that the system identifies for the checks are performed. Finally the keywords the system is capable of detecting the keywords that you provide in the paper automatically and you can also suggest other keywords which will help. If you see there's also a mesh tag which means that these are keywords which are indexed on the mesh repository to meet some of the requirements that biomedical journals can have. Finally the journal scope check within this section which is if you have chosen a target journal during the upload in which case it's for the medical journal of Cairo University your paper does not match or whether how much it matches the system will be able to deal you instantly. Additionally the system will also suggest alternative journals that will help you in your triage of which ones to submit to next. Then we have the language quality section which will give you a numeric score of how well the paper's language really fits the academic writing requirements and you will also get a quick look into the different kinds of errors that are present in the paper. So for example 9 article corrections or these are the two of corrections and the corrections are indicated as well. Then we have the plagiarism check which will be through the authenticate report as I mentioned. Once you click on this link you will be taken to the authenticate report which will obviously give you the entire report for the content that has been matched and against which source so you can cite the sources necessary and avoid unintentional plagiarism. Then we have the ethical compliance checks which will give you a quick overview of whether your paper meets these requirements. For example informed consent not present in a document or the ethical statement is not present in the document as well but the document does contain these financial disclosures and the conflict of interest again is absent. This obviously helps in quickly analyzing your paper's readiness for these ethical requirements which journals have. Then finally the technical compliance section will give you a structural understanding of how well the paper is ready for submission starting from the author names and declaring the paper to the affiliations and whether the correspondence details are present or not. And then finally the abstract till the front matter whether you have the abstract within the range which is usually preferred or whether it is structured or unstructured then the different sections used within the paper and the references as well. Interestingly this system will also be able to tell you whether the references are old or new so you can avoid review criticism for old references which weaken your argumentation. Then finally for figures and tables as well you will be able to see if there are any missing citations in the paper. That concludes the author one over a platform overview. And finally we have the open access journal finder which helps in really identifying the journal which will be suited for your paper. The system is basically trying to understand the concepts that you have used within your manuscript and also the associations between these to identify the paper which, identify the journal which is best suited and it has published, which has published different articles in the same, with the same concepts in the past. To give you also a sense of confidence that this paper is well suited for that journal that you're targeting. It's pretty easy to use the moment you add your abstract here and with your email address you'll be able to use the tool for free and get the results. I will show you a quick demonstration. It's for the abstract that I have listed here. I will just have to click on find my journal and you will see that the Worldwide Journal said that I have selected. I am getting suggestions for foot and ankle orthopedics for this particular abstract. You will also get insights into what the process for peer review looks like. This journal operates a double bind peer review process and the article processing charges and the typical publication speed that usually the journal takes and also the conference index. And you will also see the keywords that have tallied against the abstract you have pasted in the journal that has published in the past. The subject area under which your paper, your abstract really falls in and you will also find useful links for the author instruction page, the review process page and the journal scope page. For there to a board page as well. And as you will see you will get multiple suggestions ranked based on the confidence system generates and sees between the match between the abstract you have pasted here and the journal's past publications. You can also choose between different regional databases. For example, JSTATE for Japan and COAG for China. That concludes our session. Before I close just a quick overview of the OJF's unique points. As you had seen you will get these different suggestions for different journals that will match your content and obviously give you more confidence of whether the journal scope is matching with your paper's research or your research that you have conducted. And the system is designed with safeguards in place for data safety. The AI system is exclusively doing your content and the content is discarded right after. So that's a quick look. We have a large database about 1.5 million articles. And of course there is segregation for different databases as you had seen between the worldwide DOAJ and JSTATE for Japan and similarly COAG for China. So that concludes the different session for different tools we have available for authors. And I would really request you to try all of these out. You can avail all of these for free. And you know I'm pretty sure you'll find benefit and really using all of these tools to your publication process. Over to you. Thank you Stephen and Rahul. For such a wonderful and informative session we are now open to take questions. We request all the attendees to kindly send us their queries using the questions tab in the control panel. We have one question. Are the contents of the table, figures and legends checked and corrected? I think this is for Trinka. Rahul can you answer? Sure. So yes the platform will be able to detect whether you have the figure or table captions present in the manuscript and if they are present whether they have been labeled correctly and also cited in the text as well. In fact if your citations are missing the order, numerical order in the text you will also get an alert for that too. The second question is how safe are the manuscripts on the cloud? Alright that's an interesting question and of course an important one of course as well. So I will also give you a bit of context. The House of Anago, we have been working with authors worldwide for about 14 years now and we have also worked with publishers helping them really improve the quality of the manuscripts once they have accepted as well. So essentially we understand the importance of making sure that the manuscript content is safe at all times. All the communication that happens between your browser and our servers is through an encrypted channel and all the data that is stored at our servers temporarily or permanently is also within encrypted channels and through virtual private clouds. So your data is stored securely and is not accessible to anyone else. And none of the data is indexed in any other third party tool on the platform. Thank you so much for that. I would once again like to mention that audience can send us their questions using the question and answer tab. The third question is what is the percentage similarity it can detect? Alright so that will essentially depend on the content that you are checking. The system basically understands the different concepts that you have used within the paper or the piece that you have used it. And essentially the publications that have been published within on that journal or within that journal in the past. So the percentage can obviously vary from 0 to 100. 0 being no match at all, 200% being complete match. Although 100% is quite unlikely but essentially we have seen that journals which papers which have been published in the past and in the journal having that paper or similar repository. If it's a good match usually you get around 95 to 99 as well sometimes. But that depends totally on the content that you have written and the publications that the journal has made. And we have a vast repository. So essentially we have covered different subject areas from different disciplines and even different journals from different regions as well. I think we can conclude this session. Thank you Stephen and Rahul. Our attendees have certainly gained a lot of critical information from this session. We would once again like to thank all our attendees for joining the webinar. Please find the discount codes of our editing and publication support services in the chat box. We would also request you all to please fill the feedback survey displayed after you leave the webinar. Your participation will allow us to evaluate the effectiveness of our webinar. Have a good day.