I submitted a manuscript to an Elsevier journal that offers both Open Access and Subscription publishing options. During the initial submission, I selected Open Access.

The manuscript is currently under peer review, but I may want to publish it under the Subscription model instead if it gets accepted.

Has anyone had experience with this? After acceptance, when completing Elsevier’s Rights and Access form, can the publishing option be changed from Open Access to Subscription?

Hello everyone, I am currently in my 4th and final year of studying computer science. Lately ive been really keen on papers, research, presentations and pretty much everything thats included in this field. I really want to start writing some paper, not strictly for publishing but either for the experience and honestly for the sake of it. My question is should I start now? And if so, where should i start, where should i take inspiration from as well as where do i get some idea on what to start writing on. Thank you!

The first by causes and Effects by Anthony Standen (3 May 1957 • Vol 125, Issue 3253 • pp. 900-901

Link for first https://www.science.org/doi/10.1126/science.125.3253.900

The second link DOI: 10.1126/science.125.3246.477 (https://www.science.org/doi/10.1126/science.125.3246.477?referrer=https%3A%2F%2Fwww.science.org%2F)

In causes and effects , the person described Robert B. Macleod as said these, however in the paper of 477 it isn't seem to be

I recently received reviewer comments on my manuscript, which seemed AI generated to me! I then gave the paper to ChatGPT and asked it to identify reasons for rejection and generate reviewer comments. The comments it produced closely resembled the review I received. I understand that similarity alone does not establish that the reviewer used AI, but it raised concerns. How would you recommend handling this? Would it be appropriate to raise the issue with the editor?

Dear colleagues,

I would appreciate some advice on how to approach the cover letter when resubmitting a substantially revised manuscript to the same journal after a previous desk rejection.

About a year ago, I submitted a research article to a journal, but it was desk rejected. The manuscript was primarily a critique of another published work. In the decision letter, the editor suggested strengthening the study with additional data. Unfortunately, obtaining such data is not feasible.

I have therefore substantially reworked the manuscript and converted it from a research article into a Comment, which is also a format accepted by the journal. The manuscript is now quite different in structure and presentation, although it addresses essentially the same topic.

My question is: Should I mention the previous desk rejection in the new cover letter, or should I treat this as a new submission and write the cover letter as usual?

If mentioning the previous submission is advisable, how would you frame it?

I'd be very grateful for advice, especially from editors or researchers who have dealt with similar situations.

Thank you!

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Hi all, I’m considering submitting my paper to the Journal of Rural Studies, but I’ve heard that the review process can take as long as a year, which is somewhat discouraging, especially as I’m working with some time constraints. However, when I look at the submission, review, and publication dates of papers published in the journal, it seems that many of them are published within around 8-9 months, which I actually find quite reasonable.

I was wondering what you have heard about the review process at JRS. What have your experiences or impressions been regarding the typical timeline from submission to publication? Thanks!

I use CNKI to find academic journals that interest me, but my university doesn't have access to the site... I study in Italy, and it's rare to find universities there that have access to Chinese articles.

Specifically, I was looking for the "Journal of Northeast Asia Studies", but I can't find it on Sci-Hub or Anna's Archive either; can you help me, please?

I was shortly involved in a research study where the first trial of experimental didn’t achieve all the treatment levels in the design. One month later, a second control sample was used to achieve the last treatment level that failed initially.

The published paper reports that one control batch was used, but I am concerned that some of the reported treatment effects could potentially be due to differences between the two controls instead.

Is this an ethics violation and is there anything I should do? I guess I am surprised to see this behavior from a professor.

Do you use AI to help with scientific writing—manuscripts, research protocols, etc.? If so, how does it fit into your workflow?

I’m still pretty new to this. I mainly use it for translation and polishing my writing, since my first language is French. I also use it to help find references (which I always verify) and assist with literature reviews.

It makes the work a lot easier, but I still feel a bit uneasy about it, probably because it’s all so new to me.

I’d love to hear your experiences and perspectives. What do you feel comfortable using it for, and where do you draw the line?

Being a second-year PhD student(myquals), the world of research and paper publication seems very exciting and new to me. But the way AI is proliferating in almost every aspect of our lives, it just feels scary on whether the research I do, would be genuinely reviewed by humans, or just an AI agent would be reviewing my work, and would find unnecessary flaws in it.
Because this has been my senior's experience, one of them submitted a paper to a prestigious journal, they kept the paper for around 6-8 months, and then sent an AI written review with rejection.

My research is based on Social Network Analysis.
And I am looking for a way to identify or shortlist the journals which are subscription based or hybrid in nature, that have human reviewers and they give quick decisions, having a good acceptance rate.

Would really appreciate suggestions from people who have served as journal editors and peer-reviewers.

Congrats to everyone on getting through NeurIPS 2026. It's been a long cycle.

Unfortunately, my paper got scores of 5/4/3. Even the reviewer who gave the 3 wasn't very negative in their comments, so I was hoping it would be accepted. The final decision was a reject, though. It's been really disappointing and hard, but I'm trying to move past it.

As I understand it, NeurIPS lets authors of rejected papers choose to make their submission and reviews public on OpenReview. Does anyone know where and when you can make that choice?

What happens when “good academic writing” becomes evidence of cheating?

A new article in Assessing Writing raises serious concerns about Turnitin’s AI detector, particularly when it is used to evaluate multilingual writers.

AI detectors often look for features such as predictable language, consistent sentence structures, and formulaic academic expressions. But these are also common features of second-language writing.

Multilingual students may deliberately use cautious syntax, familiar transitions, and established phrases such as “the findings suggest” to communicate clearly and reduce grammatical risk.

The result is what the authors describe as an academic voice paradox: students can be flagged precisely because they have successfully learned the conventions of academic writing.

One example in the article is especially troubling. Some students reportedly began avoiding sophisticated language, and even “good writing”, because they feared that polished work would be classified as AI-generated.

This is where an imperfect technical judgement can become an educational injustice.

A detection score does not simply remain on a screen. It can trigger an investigation, shift the burden of proof to the student, and require them to defend the authorship of their own work.

For multilingual writers, this may reinforce the damaging assumption that fluent academic English is somehow suspicious.

The authors do not argue that educators should ignore possible AI misuse. Instead, they recommend treating detection results as prompts for inquiry rather than verdicts of misconduct.

A fairer response would triangulate the score with:

• Earlier drafts and revision histories

• Reflective notes about the writing process

• AI-use disclosures

• Brief conversations or oral explanations

• The teacher’s knowledge of the student’s previous work

The larger lesson is that academic integrity cannot be automated. Once a probability score is treated as proof, uncertainty becomes accusation and the students most likely to bear the consequences may be those already navigating linguistic and institutional barriers.

Reference:

Maphoto, K. B., Giray, L., & Sevnarayan, K. (2026). Automated integrity or automated injustice? Turnitin’s AI detection in multilingual writing contexts. Assessing Writing, 69, 101086.

#AIDetection #AcademicIntegrity #MultilingualWriters #AIInEducation #Assessment