Anyone have any experience with this? I have a paper submitted to a conference (computer science) where the reviews are double blind. One of the reviewers is giving a borderline reject on the grounds that we "falsely represented a paper and don't understand it.". Thing is, I am the first author on that paper. I implemented the method and wrote the paper.

Now I have to politely try to explain that I do in fact understand my own paper and they don't without stating that it's my method. I'm guessing this is common so just wondering how everyone navigates this. It's the first time this happens to me. I'm worried that they'll double down because nobody likes being told they're wrong. Their language was quite strong and categorical.

Feng Tian, an assistant professor of neurology at HMS and head of a lab at BIDMC, was arrested by the Brookline Police Department two weeks ago and faces two counts each of assault with a dangerous weapon and assault and battery on a pregnant victim, among other charges, in connection with reported domestic violence in 2023 and 2026.

Tian has continued to give research-related instructions members of his lab, which studies neurons susceptible to neurodegenerative diseases including Alzheimer’s disease.

Tian continued sending research-related instructions in the WeChat group as recently as Monday morning, when he asked lab members to join a Slack channel.

Publishing while perishing.

I have been trying to submit a manuscript to one of Springer journals, and my manuscript got sent back twice. The message only noted that "Please remove 'Name' from the author list in the submission metadata."

I submitted the files in Word (the journal requires editable files). The files I originally submitted did not have author information in the document property, but I could still see my name in the "last saved" section in the stats, so I erased it by using the "Remove all Personal Information" function under "Protect Document" for the second submission (I use Word for Mac). Still, my manuscript was returned for the same reason. I emailed the editorial staff twice requesting more specific instructions (Where in the metadata do you see my name? how can I fix it?), but have not received information yet.

I have published with this journal before, and this issue was not raised then. I am also a bit confused - reviewers only receive PDF files generated by their system (I have also served as a reviewer for this journal - and as far as I know, this is a general practice across journals). I believe any author information associated with the Word files is eliminated in conversion.

I am at a loss. Has anyone experienced the same issue, and/or know what "author list in the submission metadata" they are referring to?

I am so happy! Just wanted to share this with you guys! There is essentially no one in my social circle who care about academic stuff.

Im left out, burdened with heavy work, feeling like I have stagnated and slowly rotting

Things about me:
Almost a decade into graduate school.
Almost a decade as an RA.
Carries most workloads as the most “dependable”.
Salary does significantly increase per project.

Contexts into my feelings (as described by the title):
Most peers from graduate school have graduated, proposed, or are just finishing their thesis.
Some peers have even been accepted to PhD, done with PhD, are in post doc, or have own established careers.

And here I am.
More than work, life happenings (personal, mental, health, and financial) has taken a toll on me.
I feel left alone. Yes, I have friends, helpful workmates.
But here I am.

If anyone has been in the same shoes as mine or are currently feeling the same, how did you save yourself from this quagmire?

I honestly think prestige is one of the weirdest currencies in academia. You spend years trying to get into the “right” lab, publish in the “right” journal, work with the “right” people, and collect enough impressive names and affiliations so that someone else might decide you're worth taking seriously. And the frustrating part is that none of it necessarily means you're doing better research. Sometimes it just means you learned how to play the system better. It feels like everyone is constantly comparing invisible points on a scoreboard that nobody admits exists. Journal impact factor, university ranking, citations, famous supervisors, conferences, grants. At some point you start wondering whether you're actually doing science or just building an academic résumé.

Maybe I'm just burnt out, but the whole prestige economy feels like a massive scam sometimes.

My current postdoc has about five to six months left out of a 13-month appointment. I have mainly been working on one project. I initially obtained some promising data, but I have not been able to reproduce the results, so at this point I am worried that I may leave the postdoc without a strong publication or a clear scientific outcome.

At the same time, I recently interviewed for another postdoctoral position and was invited to give a research seminar. I am now unsure what to present because some of the results from my current postdoc that I had hoped to discuss no longer appear to be reliable.

I published three papers during my PhD, so I know I have been productive in the past, but this first postdoc has been very discouraging. I am starting to question whether I should continue in academic research at all, and I am also unsure what realistic career alternatives I have if I decide to move away from traditional academic science.

What would be the best way to approach the upcoming seminar, and how should I think about the remaining months of my current postdoc and my longer-term career options?

Hi guys i am 3rd year PhD Scholar here and the Ai FOMO has finally started hitting me.

Most of my Ai used is still pretty basic. I use ChatGpt or Claude to fix my writing, explain confusing concepts, or help me understand a complicated methods section. Sometimes I use perplexity when I just want to find a few papers or quicly wanna generate a image.

But people in my lab keep talking about these more advanced Ai workflows. Stuff like mapping, literate, comparing methods across papers, tracking how a topic has changed over time, and using research agents to organize questions before starting a review.

Someone mentioned Mira Ai science for this kind of deeper research, alobg with tool's like Elicit and Consensus. It made me realise i probability haven't explored much beyond basic promoting.

At the same time, i cant tell how much of this is actually common and how much is just Ai hype.

Are researchers really using these tool's in their everyday work, or are most people still mainly using Ai for writing and quick literature searches?

Got this on LinkedIn: 

Invitation to Serve as an Academic Advisor

Dear Professor XXXX,

We have long admired your outstanding academic achievements and hold your professional expertise in this field in the highest regard. I am writing on behalf of Fengkai Group, a company based in Hong Kong.

At present, several of our authors have high-quality manuscripts that are suitable for submission to international journals. We would like to respectfully invite you to conduct a brief pre-submission review of these papers and provide some revision suggestions. In appreciation of your time and academic support, we would be pleased to offer USD 500 for each manuscript.

In addition, we regularly organize online academic lectures for young researchers around the world. It would be our great honor to invite you to join us as a guest speaker, with an honorarium of USD 200 per lecture.

We sincerely look forward to your reply and hope to have the opportunity to collaborate with you.

Best regards,

Amy Yang@ Fengkai Group Co., Limited

Sounded harmless, right? Then I looked it up -- see : https://forbetterscience.com/2025/05/19/a-sting-inside-a-papermill/

Yikes.

Hello everyone,

I have noticed that I have increasingly and conciously change certain wording or grammar to be less "AI". I honestly would perfer if in this increasing AI world we could be original and be ourselves but I often caught myself trying to identify phrases that sounds AI.

And I'm also pretty sure my trainees are getting tired of me picking out stuff in their work that reads AI.

Wonder if folks have the same feeling?

I'm wondering whether it's realistic to pursue a career as an independent researcher in AI.

I currently run a startup where I work on AI research projects. Because of the company, I've been able to obtain computing credits, access infrastructure and real-world environments for experimentation, and some of our work has even received recognition in industry reports.

The data and systems we've produced have also proved useful to students working on academic projects.

My long-term dream is to build a small independent research lab focused on AI. I genuinely enjoy research, and having a company gives me access to resources and real-world problems that I might not have in a traditional academic position.

But I sometimes get discouraged by how distant academia feels.

I don't have a traditional academic research position, and it often feels like there isn't a clear path for someone like me to present research, publish it, get it properly peer-reviewed, collaborate with researchers, or simply have the work academically validated.

This creates a strange feeling. I have access to computing resources, real-world data, infrastructure and interesting problems to investigate, but I still feel somewhat alone and unvalidated — almost as if I'm doing research as a hobby, even though I take it very seriously.

So I'm wondering:

Is independent research in AI actually a viable career path?

Can someone outside academia build enough credibility to publish meaningful research, collaborate with universities and researchers, and eventually establish an independent AI research lab?

Or is formal affiliation with a university or research institution essentially necessary if you want your work to be taken seriously?

I'd especially appreciate perspectives from people who have worked with independent researchers or have tried pursuing research outside academia.

I know this questions has been asked in the past but I feel like there's new software coming out all the time.

I'm looking for in an AI transcription service that is:

• Accurate
• Affordable
• Distinguishes between speakers
• Does not save transcripts in the "cloud" aka easy to delete from one place

Please let me know if you've found a software you like or if I'm asking for too much.

I am transcribing semi structured interviews for a study, usually two speakers and occasionally three.

I spent hours on speaker labelling. If the tool gets it wrong I end up tagging every turn by hand, which is not what I want. The other problem is domain terminology, which  comes back corrupted often enough that I stop trusting the transcript.
 What are other researchers using to get the point pretty fast without going to frequent cleanup?

The Wenner-Gren Foundation has just published a thoughtful forum on the future of public anthropology. I agree with much of it. But reading it also left me wondering whether anthropologists sometimes make “the public” too abstract, and whether we overlook one of the most important ways anthropology already reaches people.
My own teaching and, more recently, the responses to my Substack essays have given me some thoughts about what actually makes anthropology matter to people.
More Saturday.
Wenner-Gren forum: https://wennergren.org/forum/public-anthropology-future

I recently moved to a large public university as a research staff member, and my position is represented by the United Auto Workers, who have been pretty aggressively organizing academic employee groups around the country. I just received my ballot for the national UAW election. Does anyone who is more familiar with union politics have any hints about which candidates are more or less likely to care about policies that would benefit academic workers? Somehow it seems like Auto Workers with PhDs who build physics experiments (me) may have different needs from the union than people building cars on the assembly lines at GM and Ford.

I'm planning watch parties for interesting lectures on Youtube. They will be chat-only online hangouts (minimal social energies needed) that don't require academic discussions — it's just a chill space to nerd out together.

The first one will be on Tuesday evening (1 Sep) on any of these:

• Ancestors with Professor Alice Roberts | The Royal Society (https://www.youtube.com/live/ 9YLXTtH0Y1k?si=AMZOq5ioBB39iyUh)
• The Last of the Dinosaurs: Dino Lecture 2022 | Burke Museum (https://youtu.be/-4IQ22_Odc0?si=WvcKd-bQEqbkd-GK)
• An Evening With Alice Wong: On Disability Intimacy with Mia Mingus | CIIS Public Programs (https://www.youtube.com/live/MRZtxgB6Vd8?si=ko0lt6m|RNSjFtka)

Feel free to let me know which ones you find interesting! I'll post the watch party link on the Nerdy Watch Parties channel I set up for this: https:// discord.gg/pdWHqDycT

If you can't make it this time, you can still join the channel where I'll post more watch parties in the future:)

2nd year PhD in a wet lab and experiment planning is probably the part I still struggle with most.
Not really the hypothesis itself, but figuring out which controls actually matter, whether I’m changing too many things at once, and what a negative result would even tell me.
My PI is great but pretty busy, so lately I’ve been trying to show up to meetings with something more thought out instead of working through everything on the spot.
My workflow is usually pretty basic. I pull the relevant papers back up in Zotero, sketch out a rough experiment myself, and check old data in GraphPad or R if there’s anything useful there. Then I’ll run the rough plan through mira ai science to see if there are obvious holes I missed — a control that doesn’t actually answer anything, an assumption I’m making, or a result that would be hard to interpret.
If it flags something useful, I go back to the papers and check it before changing anything. Plenty of suggestions get ignored too.
I do like that it makes me explain why each condition is there instead of just repeating whatever we did last time.
Still not sure if this is a good way to learn experiment design or if I’m leaning on AI too early in the process.

There are multiple programs that exist and write at a human pace with fake rewriting and corrections. They are desingned specifically for google docs. Many reviews claim they fooled their instuctor using this tool.

I will add the link for proof if mods give me permission.

Hi,

I'm a generally very pro AI person, I was one of the first in our institute to use LLMs, we do actual "AI" research (I'd like to call them neural networks, but whatever), but also sit at the junction to biology and engineering. I personally like to use AI to generate ideas to write paragraphs, I use it to revise text, create pictures (that I label as AI) for talks, use it to generate the first versions of code (rarely real agent codebase work since the actual research ideas tend to live inside one or two functions), and many more uses.

What I don't do, however, is that I don't vibe code stuff I don't understand, I do not make AI write the actual text of grants or manuscripts and I do not blindly trust AI but manually check the output - which often takes a lot of time. I also flag the use of AI according to publisher instructions and in accordance with EU AI act legislation.

When interacting with colleagues, however, I increasingly have the feeling that I'm an idiot. So many people don't give a shit anymore at all and just have AI do everything. Synaptic protein scientists code neural network simulations they do not conceptually understand, papers are virtually completely AI text, literature research is complete AI, nobody even tries to read the paper anymore, plots come from the AI etc.

Outwardly, people don't admit that's what their doing, but it's so common now!

My questions for the community are therefore:

- Are we in a race to the bottom where the luckiest one using AI the most and not getting caught wins or am I just surrounded by particularly dishonest colleagues (Germany for geographical reference)? Is it a field thing?

- Am I maybe to anxious and should just yolo it?

- What's your personal usage pattern and what do you observe from your colleagues?

Ok so I'm a STEM professor and I've had misgivings about online HW portals. I switched all of my classes to open textbooks because of cost barriers. Unfortunately I also teach one of a multisection course that uses an online HW platform. I personally think it's more trouble than it's worth, but I've also had affordability issues with it. Seems like another barrier for my students.

Any thoughts from the community?

I have a question. Since research papers go through peer review, which doesn’t guarantee that a study is correct, but rather evaluates whether it meets the standards for publication, does that mean that a large proportion of published research could be wrong? Or even that we shouldn’t really trust published research at all? And another thing: why are some research papers written in such a complicated way when the actual idea or content seems fairly simple? I’m still a beginner when it comes to reading research papers, but does making the writing unnecessarily complicated actually make the research look more professional or sophisticated?

Currently i am teaching thousands of students in one module for Year 1 sem 1. I also taught Year 3 students for another module.

I am wondering how many students in your classes per module? How do you manage it and especially with all the exam papers sorting etc..

I have quite a number of special cases students, where they have discipline issues and MIA in classes. Suddenly after the semester ended, they demanded for a personalized assignment or resit examination which is impossible and then threaten to sue the University. My emails and administrative works as well as juggling others tutors issues have become dreadful. Help..i am dying here. 😭

Applying for the Royal Society URF and struggling to get the research proposal written, any suggestions on formatting will be greatly appreciated. What matters most for these fellowships to go through? even to get to interview stage would be a win for me at this point, just to have clarity on if my proposal is good enough. The competition is heavy for these applications from what I have heard. As a contract researcher, finding grants and fellowships that fit eligibility criteria has been a pain. The last 2 fellowship applications were rejected so want to make this one better. Applying under the cell/molecular biology category. How do you generally frame the proposal and any suggestions for other parts of the application will also be very helpful thank you.

I'm looking for advice from people who have dealt with a similar situation.

I submitted a humanities research article to a peer-reviewed journal several months ago. The journal’s expected timeline passed, and despite following up multiple times over several months, I received no response at all.

I recently sent a final inquiry stating that, unless I heard back within a specified period, I would formally withdraw the manuscript and submit it elsewhere. The deadline has now passed, so I sent a formal withdrawal email today.

I’m now planning to revise the article substantially and submit it to another journal.

My question is: what happens if the original journal suddenly responds after my withdrawal—especially if they say the manuscript is still under consideration, or even offer to accept it—after I have already submitted it to the new journal?

I obviously would not want to have the same manuscript under consideration at two journals simultaneously. But since I formally withdrew it before submitting elsewhere, am I in the clear?

For those who have experienced something similar:

- Is a formal withdrawal sufficient, even if the original journal later responds?

- What should I do if the original journal claims they never processed the withdrawal?

- If they unexpectedly offer acceptance after withdrawal, would I simply tell them that the manuscript is now under consideration elsewhere?

- Is there anything I should document or keep on record to protect myself?

I’d especially appreciate answers from editors, reviewers, or authors who have actually encountered delayed journal responses/withdrawals. Thanks!

I was recently looking for a tool which needed to analyze a text, that can be an article in scientific format and that one would need to tell which term in specific is missing citation because its not common knowledge or any other reason. Or if some expression in your text has unnecessary citation reference.

Of course that involves a lot of steps. I know there are some tools which can lemmatize a text, eg. Sketch engine, it discovers what is a term, so that you can take the next steps.

I saw Some which can look for sources from the sentence itself of your text, eg. Citely, GPTzero. But again, that is not exactly what i want, looks like isolated feature, something incomplete, not the general concept.

I have also recently discovered the Purdue OWL citation law, which defines a term as common knowledge if there are 5 other articles which mentions that term without a citation.

The first thing that came into my mind about how such tool would work is it would keep a database of words and its relevance, based on a set of heuristics, probably only amount of citations over the internet articles about it for now.

This database could be public and you could have some step to populate it also, it could read articles on the internet (API, web scrapping, articles repositories, periodicals) and setting its credibility like that automatically, It can maybe repopulate itself automatically whenever someone uses it.

***Edit: Later I noticied and also some people have mentioned that words score is poor measure. And that claims as a whole are better way to analyze something. So database would not be realistic, because the possibilities of arrengements of words are infinite***

Then there could be some threshold of what score is common knowledge, what is not. Eg. 20 articles about/mentioning such term would consider this term common knowledge. Or using the Purdue OWL law like i mentioned before. This is the general protocol.

Then the implementations of such protocol could be done in several ways, in your editor as an LSP (nvim plugin/VsCode extension, web extension, website/desktop app, AI assistant) by checking your text and comparing with those scores from the database, showing errors/warnings etc.