Check out these guides to learn everything you need to know before you begin your research or start your manuscript. They include everything from who can submit to eiRxiv, the types of manuscripts we accept, and how to develop a research project, to additional considerations for certain research topics and our expectations for academic honesty and AI use. Please read them in full before you start researching or writing!
On a scientific manuscript, different authors may have different roles and responsibilities. Different journals or preprints may also have different rules for who can publish with them, and how each author needs to be involved. Make sure you read and understand eiRxiv’s full author eligibility information below before you begin your manuscript.
Because we are a preprint for students, eiRxiv expects students to be the main creators and writers of any work that is submitted:
To comply with laws to protect minors online, such as Children’s Online Privacy Protection Act (COPPA) in the United States, we require that an adult serve as the corresponding author, sometimes known as the last author or senior author.
Additional student and adult authors should also be listed if they helped significantly with 3 or more of the following:
All individuals who meet three or more of these conditions must be listed as authors on the manuscript. All authors must also approve of the final manuscript, give consent for it to be posted, and take responsibility for resolving any issues related to the accuracy or integrity of the research. If any individual who meets these requirements does not want to be an author, please have them document in writing their decision not to be an author – our editors may ask you for this.
On the other hand, contributors who don’t meet all of these conditions should not be listed as authors, and can instead be listed in the acknowledgements.
When you submit your manuscript, your title page will need more than just a list of authors. See below for the information you need for each author, and how to format the authors on your manuscript.
Affiliations
All authors must list an affiliation (the place where they work or where the work was done).
Author order
Scientific manuscripts list authors in order based on how much they contributed to the work. This means that the author listed first did most of the work, and the author listed last did the least. In fact, the last/corresponding author sometimes only helps with designing the experiment and mentoring the other authors as they write the manuscript.
If any student authors did equal amounts of work, you can show this by placing an asterisk (*) after their name and the statement “these authors contributed equally to this work” underneath the list of author affiliations. If any senior authors contributed equally, please use the same formatting as for student authors, but use the dagger symbol (†) instead.
As an example, let’s imagine the following authors contributed to a manuscript that they are trying to post on eiRxiv: Jaylen Smith, Sarah Johnson, Angel Ruiz, Marcus Gold, and Julie Zhang.
In this example, the authors and their affiliations would be listed like this on the cover page when they submit their manuscript:
Jaylen Smith1, Sarah Johnson1*, Marcus Gold2*, Julie Zhang3, Angel Ruiz4
1Allan Bayer High School, Smithsville, Alabama
2Corbin Downs High School, Citytown, Georgia
3Emory University, Atlanta, Georgia
4University of Florida, Jacksonville, Florida
*These authors contributed equally to this work
Changing author order after submission
To ensure a smooth submission process, we ask that you ensure all the necessary authors are listed, they are in the correct order, and they all agree to submitting the manuscript before you submit your manuscript to eiRxiv.
If you would like to add, remove, or change the order of authors, we need written consent from all authors. We reserve the right to reach out directly to any authors impacted by these changes.
Because each manuscript is posted with a permanent DOI, authors cannot be added, removed, or changed after the manuscript is posted.
Have you ever wondered why things happen the way they do? Or wanted to figure out how something works? That’s what doing a research project is all about! In science, you get to ask questions, test your ideas, and discover answers, like a detective solving a mystery. These are the phases you’ll go through when developing a research project.
Every research project starts with a question. Ask yourself: What am I curious about? What do I want to discover? What problem do I want to solve? A good research question is clear and specific. For example, instead of asking “Does music affect people?” you could ask, “Does listening to classical music while studying improve knowledge retention?” During this stage, it is also important and helpful to read about what scientists already know about your research question.
Doing research is like being a detective: you ask questions, gather clues, and figure out what the evidence tells you. The most important part is staying curious and having fun while learning!
Once you decide to answer a research question, the next step is to plan how you will find the answer – in other words, you design your experiments. For your experiments, think about what you will manipulate (the variable) and what you will measure (the outcome). For example, if your research question is about music and memory, your variable could be the type of music, and your outcome could be the number of correct answers on a memory test. Use our Statistics Guide to help you plan how you will collect and analyze your data before you start your experiment.
After planning, it’s time to do the experiment! You collect data carefully, making sure to accurately document everything you observe. To make sure your data are reliable, you need to repeat your experiment several times. A good rule of thumb is at least 3 trials for each condition (called replicates). More trials are even better if you have time and resources.
Once you have collected your data, you can organize your data into tables or graphs so it’s easier to see patterns or differences. You can also use statistics (link to guide) to determine whether your results happened by chance, or because you’re observing a consistent pattern.
Once you analyze your data, you can think about what your results mean. You can ask yourself questions like: Did the results match what I thought would happen? Did anything surprise me? If your experiment didn’t work as planned, that’s okay! That’s normal in science. What matters most is what you learned from your project. You can suggest ways to improve the experiment or come up with new questions to explore. That’s how professional scientists make discoveries: by learning from both expected and unexpected data. Every experiment is a chance to discover something new, even if the results aren’t what you expected.
Decide who you want to share your research with, and how you want to communicate your idea with them. Sharing your science can take many forms: conversations, presentations, social media, posters, scientific journal articles, preprints, and more!
At eiRxiv, we require every manuscript to have a hypothesis. Although review articles can be very useful, please note that eiRxiv does not accept review articles.
Why does eiRxiv have a hypothesis requirement?
Scientific manuscripts can take many forms: hypothesis-driven experiments, review articles, commentaries, mathematical modeling, theory development, and more. All of these types of manuscripts can meaningfully contribute to scientific knowledge.
At the same time, most scientific journals and preprint servers also have a limited “scope” – in other words, they place limits on the topics and types of articles they accept. This allows the journals to provide more tailored and meaningful feedback to support the authors
For eiRxiv, we limit our scope to manuscripts with a clear hypothesis that is tested by student authors. Like the Journal of Emerging Investigators (JEI), we believe generating and testing hypotheses helps authors develop thoughtful experiments and understand the scientific process. We also place limits on certain topics like AI/Machine Learning and Emerging Public Health Topics (see below for more details).
✅ Tips for Creating a Good Hypothesis:
❌ A Hypothesis Should Not be:
For detailed hypothesis requirements, please watch this video created by Akshya Mahadevan, JEI’s current student advisory board member. Thank you, Akshya!
To help you develop and refine your research, check out the following examples of acceptable and unacceptable hypotheses for general research questions:
✅ Acceptable Hypotheses | ❌ Unacceptable Hypotheses |
I hypothesized that adding fertilizer would increase the growth rate of bean plants. [This is a good hypothesis because it makes a clear prediction you can test: does adding fertilizer make bean plants grow faster?] | I think fertilizer would be good for plants. [This hypothesis is vague because it doesn’t say what kind of plants or fertilizer and how ‘good’ will be measured.] |
I predicted that listening to classical music while studying would improve memory test scores. [This is a good hypothesis because it is testable and compares two situations (with vs without music).] | I predicted that listening to classical music would help students. [This hypothesis is not specific; it doesn’t say how music would help students.] |
I hypothesized that this new type of snail would genetically belong to the Cepaea genus. [This hypothesis isn’t about the author and can be tested using genetic techniques and statistical analysis.] | I hypothesized that I discovered a new species of snail. [This statement is about the author and is just about characterizing a new species; it is not a hypothesis being tested] |
Our study tested whether exposing submerged concrete to higher levels of atmospheric carbon dioxide would make it less structurally stable. [This hypothesis is simple, testable, and focuses on just one hypothesis.] | We tested whether increased atmospheric carbon dioxide would lead to impaired structural stability of submerged concrete and whether patterns in website usage could predict individual carbon dioxide emissions. This hypothesis is too complex, and tests two distinct hypotheses] |
✅ Acceptable Hypotheses | ❌ Unacceptable Hypotheses |
I hypothesized the size of a wind turbine would affect how much electricity it produces. [This is a good hypothesis because it is clear and measures how one variable (turbine size) affects another variable (electricity output).] | I hypothesize that I can build a wind turbine. [This is unacceptable because it’s about what you can do, not about testing a scientific question.] |
We hypothesized [new method] could measure pH levels more accurately than the standard glass electrode method. [This hypothesis is acceptable because it clearly compares two methods and predicts measurable outcomes.] | We hypothesize that we can develop a new method for quantifying pH levels. [This hypothesis is unacceptable because it focuses on your actions rather than a clear and testable question] |
We predicted that iron reinforced with ceramic particles could withstand more pulling force than regular iron. [This hypothesis is acceptable because it compares two types of iron. It also specifies what can be measured and predicts a testable outcome.] | I think adding ceramic particles to iron is interesting and I want to see what happens. [This is not considered as a hypothesis because it doesn’t predict a measurable outcome or specify a clear question. It focuses on your interest rather than a testable question.] |
✅ Acceptable AI Hypotheses | ❌ Unacceptable AI Hypotheses |
I hypothesized that people’s personality and social support would affect how they handle earthquake stress. [This hypothesis takes about a relationship between personality, social support, and coping with earthquake stress, rather than on the AI or method used to study it. ] | I hypothesize that I can make a new large language model to predict how people will respond to earthquakes. [This does not meet our requirements because it is a statement about whether or not the author can create a model, and the hypothesis is about the model itself – not about answering a scientific question] |
I predicted that typing patterns on a tablet could encode digital markers that can reveal attention levels in adolescents. [This is acceptable because it is studying the relationship between typing patterns and attention levels. The focus here is not on the AI or method used to detect it] | I predict that changing a factor in a common AI autocorrect program allows it to more accurately assess typing patterns. [This hypothesis focuses on optimizing a machine learning model, rather than on using it to answer a scientific question.] |
I tested whether changes in gait and limb movement can slow the progression of Parkinson’s disease-related motor symptoms, as predicted by mathematical modeling. [This hypothesis is acceptable because it focuses on a measurable biological phenomenon (gait and limb movement) and its effect on disease progression – it doesn’t focus on the modeling technique] | I hypothesize that my new modeling approach correlates gait changes with slowed progression of Parkinson’s disease progression more accurately than existing models. [This hypothesis focuses on the model, not on the biological research question. ] |
In parallel with our hypothesis requirement, eiRxiv does not accept manuscripts that simply introduce an invention, new experimental method, new computational method, or a new machine/deep learning or AI algorithm. We also do not accept manuscripts that simply optimize a machine/deep learning or AI algorithm. No matter how impressive these manuscripts may be, they do not meet our hypothesis requirement and fall outside the expertise of our editorial staff.
In short: A new or optimized invention/model/method (whether AI or not) can be a tool for evaluating your hypothesis or research question, but it should not be the subject of your hypothesis.
In some cases, you might be able to convert your invention, method, or machine learning research into a hypothesis-driven manuscript by using your device, algorithm, or model to experimentally address a scientific question. Instead of being about your invention or model, your hypothesis should instead predict what you would scientifically find with your model, and then test your model.
Below are examples of acceptable and unacceptable hypotheses for engineering projects:
In addition, many AI and machine learning based manuscripts are simply outside the expertise of eiRxiv staff and reviewers. As a result, we cannot appropriately evaluate or provide meaningful feedback on many AI, Machine Learning, or Large Language Model manuscripts. Manuscripts where AI/ML/LLM is the subject of the hypothesis, rather than a tool to evaluate a scientific hypothesis, will not be accepted.
Below are examples of acceptable and unacceptable hypotheses for AI/ML related topics:
If you have any questions about your hypothesis, please reach out to submissions@eirxiv.org.
If students’ research involves vertebrate animals or human participants, they must follow the Intel International Science and Engineering Fair (ISEF) guidelines. This means students need to obtain approval for the project before starting their research.
Approval may come from one of these groups below:
Institutional Review Board (IRB): a group of people who protects the rights and safety of people who participate in research.
Students need approval for studies involving vertebrate animals unless all the following are true:
If the research does not meet all three conditions, students need approval from a SRC or IACUC.
Students need approval for studies involving humans (including interviews and surveys) unless the project is one of these exceptions:
If the research does not fit these exceptions, approval is required from an SRC or IRB. Please see the full ISEF guidelines for human-subjects research for a more comprehensive description of requirements and SRC/IRB review criteria.
Note: While we follow ISEF guidelines in general, there is one notable exception where JEI has stricter guidelines. If the student author(s) is/are the only human subject(s) involved in the research project we DO require IRB/SRC approval for these studies. This is to ensure that the student(s) is/are not proposing any experiments that may be harmful to them physically or mentally.
Students will need signed approval letter from the institution’s IACUC (for animal research) or IRB (for human research) is sufficient. Please consult with your institution for their policies, procedures, and forms.
Students need to form a SRC. An SRC must have 3 people: an appropriate expert (e.g. veterinarian for animal research, or medical doctor for human research) , an educator (e.g. a teacher who understands science and education), a school administrator (e.g. principal). The SRC cannot include students’ parents, research mentors, anyone listed as an author on the manuscript, or students’ family members. One person cannot serve multiple roles. In addition, eiRxiv cannot form a SRC for students or give students names of people to be on a SRC because this would create a conflict of interest.
eiRxiv accepts the SRC Approval forms (Vertebrate Animal Research SRC Approval Form; Human Subject Research SRC Approval Form) recommended by The Journal of Emerging Investigators editorial team.
If a student’s research involves human participants and does not meet the exemptions listed above, participants must give informed consent. This means each person who takes part in the research agrees to participate by signing a form that explains the project, what they’ll be asked to do, and how the data will be used.
When adult authors submit manuscripts to eiRxiv on behalf of student authors, they must include a blank copy of the consent form.
Because eiRxiv aims to be a good steward for publicly available scientific knowledge, we exercise extra caution when publishing research on rapidly changing topics that could have a large impact on public health. As such, we utilize the same public health guidelines as the Journal of Emerging Investigators.
All manuscripts submitted to eiRxiv undergo a prereview screening. Those that touch on emerging health topics (e.g. COVID-19, emerging disease outbreaks), proposed therapeutic strategies, or the evaluation of existing products will receive extra scrutiny from our leadership team. The leadership team will evaluate the manuscript based on the scope/severity of the emerging public health issue, the implications of the research, and whether the research is reported in an unbiased and legally compliant fashion.
Depending on the results of this evaluation, the manuscript may either 1) be allowed to continue; 2) returned to the authors with required edits before posting; or 3) not accepted for posting.
(per the Journal of Emerging Investigators)
Due to the complex and quickly changing nature of COVID-19, eiRxiv is not currently accepting manuscripts that focus on or have implications for the following topics:
We recognize that COVID-19 is an enduring public health threat to the global community that has and will continue to motivate and influence many students’ research projects. If your manuscript is related to COVID-19 or SARS-CoV-2 and you believe that it is not covered by the above restricted topics, please email us before you submit your manuscript at submissions@eiRxiv.org. Unless otherwise approved, all other COVID-19 manuscripts will be returned to the authors by our editors. As more information becomes available regarding COVID-19, we may update the above restrictions. Although these guidelines refer to COVID-19 specifically, similar guidelines and precautions may be taken for other emerging health issues.
Note: Similar guidelines may be applied during ongoing outbreaks of any disease, whether novel or not.
Please only refer to manufactured products in your manuscript using their generic or non-proprietary names (e.g., “acetaminophen”, not “Tylenol®”; or “facial tissue”, not “Kleenex®”). Mentioning specific brand names in your research can leave the author open to legal action by the manufacturer.
You may refer to the supplier or manufacturer once in your Methods section (e.g., “semaglutide manufactured by Novo Nordisk”, not “Ozempic®”). Manufacturers should not be mentioned outside of the Methods section.
Any manuscripts that mention products by their brand name, or manufacturers outside of the Methods section, will not pass prereview.
Scientists are expected to be truthful and responsible in research and writing. All authors for eiRxiv should make sure their work is their own and give credit when using other’s ideas, results, or images. Basically, if it’s not common knowledge or your own original idea, you need to cite it. eiRxiv does not tolerate plagiarism, which is using another person’s work without crediting the source.
That said, we also understand that plagiarism can sometimes happen unintentionally – not because authors are intending to plagiarize, but because they simply don’t understand what does or doesn’t constitute plagiarism and don’t take enough steps to prevent it. For more information on what plagiarism is and how to avoid it, as well as best practices for incorporating and citing ideas from your sources, please read JEI’s Academic Honesty guide.
eiRxiv also DOES NOT tolerate authors making up data or results, or falsifying any supporting documents (signatures, agreements, or permissions). Scientific integrity is the backbone of the scientific community. Falsifying results seriously damages the trust and reputation of scientists as individuals and the scientific process as a whole and can have legal consequences for the authors. Maintaining scientific integrity is extremely important to be respected and valued within and beyond the scientific community.
Plagiarism, failing to give proper credit, and/or falsifying results may result in your manuscript failing prereview or being publicly withdrawn. Authors who seriously violate these academic honesty expectations may be banned from all future publishing opportunities with eiRxiv and JEI.
At eiRxiv, our goal is for students to develop their own unique scientific voice. We believe that first-hand experience with developing ideas, creating hypotheses, conducting research, and writing about it themselves is the best way for students to develop as scientists and communicators.
With this in mind, students may use AI tools to help with grammar and spelling after they draft their manuscript. However, AI must not be used to create or write the scientific content of a manuscript. Students must summarize previous studies, perform the experiments, analyze and interpret data, and draw conclusions themselves.
For additional information on manuscripts that use AI as the tool for conducting experiments or analyzing results, please see our hypothesis requirements.
