Preprint landscape: servers, post-publication review, and the moving boundary

Last updated: 2026-05-20

Synthesis

The preprint ecosystem has expanded from a narrow physics-and-CS convention (arXiv, founded 1991) into a discipline-spanning infrastructure with substantial — and still-evolving — overlap with traditional journal publishing. By 2024, biomedical preprint servers were hosting hundreds of thousands of papers annually; COVID-19 (2020-2022) compressed roughly a decade of biomedical preprint normalisation into two years [1, 2]. The current landscape encompasses archive-style preprint servers that provide minimal moderation and lasting time-stamped citation (arXiv, bioRxiv, medRxiv, ChemRxiv, EarthArXiv, PsyArXiv, SSRN, OSF Preprints), post-publication peer-review platforms that add a refereed layer on top of preprints (PCI / Peer Community In, Review Commons, F1000Research, eLife’s post-2022 “reviewed preprints” model), and journal-policy variation about preprints that ranges from required pre-submission to outright prohibition [3, 4].

The decision an author faces is no longer just “where do I submit?” but a multi-part one: do I preprint? where? before, after, or instead of journal submission? do I want pre- or post- publication peer review? what does my target journal allow? These questions have substantively different answers across fields (physics and CS have preprint cultures decades older than the journal venues that aggregate them; clinical medicine still treats preprinting cautiously because of patient-decision implications), across career stages (preprinting carries different cost-benefit calculations for trainees vs. established researchers), and across funder requirements (NIH, Wellcome Trust, cOAlition S funders all have specific preprint and open-access requirements that interact with venue choice).

For an automated venue-fit recommendation, the consequence is that the preprint layer cannot be a one-size answer. The author needs to be asked whether preprints are in scope for them, and the recommendation has to account for the chosen preprint server’s interaction with the recommended journal’s preprint policy. The landscape moves fast enough that the right grounding posture is to maintain principles in this note and verify specifics at invocation time.

Evidence and frameworks

The major preprint servers

arXiv (Cornell, founded 1991 by Paul Ginsparg) is the original and the model. Initially physics, expanded to mathematics, computer science, quantitative biology, economics, statistics, and several others. arXiv applies endorsement-based moderation (new authors must be endorsed by an existing author) and minimal subject-area screening; the time-stamp is the durable contribution. By 2024, arXiv hosted roughly 2.5 million papers across categories [5, TODO verify exact current count]. The CS subfields have built an entire publication culture around arXiv-first posting; physics and math have done so for longer.

bioRxiv and medRxiv are operated by Cold Spring Harbor Laboratory Press. bioRxiv (launched 2013) covers preclinical and basic biology; medRxiv (launched 2019, joint with BMJ and Yale) covers clinical research. Both apply a screening process focused on excluding non-research content, plagiarism, and obvious methodological problems. medRxiv adds a clinical-screen layer to guard against papers that could mislead patient decisions [6]. COVID-19 made medRxiv a central piece of the public-health information infrastructure and surfaced both the value (rapid dissemination of preliminary findings) and the cost (misinterpreted preprints driving public policy) of biomedical preprinting [7].

ChemRxiv (founded 2017, jointly run by ACS, RSC, GDCh, CCS, and CSJ) is the chemistry-discipline preprint server, with moderation similar to bioRxiv’s. EarthArXiv (2017, EarthRxiv governance) covers Earth and planetary sciences. PsyArXiv (2016, hosted on OSF) is the psychology preprint server with broader social-sciences uptake. SSRN (1994, acquired by Elsevier in 2016) is the social sciences and economics preprint server with substantial uptake in finance, law, and accounting but increasingly contested governance after the Elsevier acquisition [8].

OSF Preprints (Open Science Framework, Center for Open Science) provides a multi-disciplinary preprint platform with moderation per discipline. The OSF model is more meta-infrastructure than single server; many discipline-specific preprint servers run on OSF (PsyArXiv, SocArXiv, LawArXiv, others).

For an author choosing a preprint server, the relevant axes are: discipline scope (does this server cover your field?), moderation rigor (will format/scope problems be caught before your paper is publicly time-stamped?), license and reuse terms (CC-BY, CC-BY-NC, and variants — these matter downstream for journal submission), indexing (Google Scholar yes for all major servers; PubMed-relatedness varies), and the target journal’s preprint policy.

Pre-publication vs post-publication peer review

The pre/post-pub distinction is the second axis. Traditional journal review is pre-publication: a manuscript is reviewed before it appears in the venue. Post-publication review platforms add an explicit layer on top of preprints in which the time-stamped preprint is the durable record and review happens after public posting. Several variants matter:

PCI / Peer Community In [9] is a community-run system in which discipline-specific “Peer Communities” (PCI Evolutionary Biology, PCI Ecology, PCI Neuroscience, others) recommend preprints based on full peer review. The recommended preprint is a recognised endorsement; no APC, no journal submission required. Many mainstream journals accept PCI-recommended preprints as fast-tracked submissions or accept them outright [10]. PCI is strongest in ecology and evolutionary biology and is expanding.

Review Commons [11] is a refereed-preprint service that provides journal-independent peer review on bioRxiv preprints, with the resulting reviews portable to affiliated journals (EMBO Press, eLife, others). The author receives reviews; the journals receive reviews and decide independently whether to accept based on the existing review record. The model is “review the science once, decide at multiple journals” — the inefficiency of multiple re-review cycles is reduced.

F1000Research [12] is a post-publication peer-review platform where papers are published openly after editorial check (not peer review), then reviewed openly by invited reviewers whose names and reports are public. Articles can be revised in response to reviews; the final status of an article is “approved” (1+ reviewer recommendations), “approved with reservations”, or “not approved”, visible to readers. F1000Research has strong uptake in clinical research, gene/genome papers, software/method papers, and is the canonical reference for the post-pub review model.

eLife’s post-2022 model [13] is the most consequential recent shift. eLife eliminated the accept/reject decision in late 2022; under the current model, eLife reviews any preprint the editors select for review and publishes the resulting Public Reviews alongside the preprint as a “reviewed preprint”, with no final acceptance gate. The author can revise; eLife continues to review revisions; the preprint and its review record are the publication. This is the most aggressive existing implementation of the post-publication-review model at a high-impact journal.

The pre/post-pub choice is not just a venue choice; it is a strategic choice about timing (rapid dissemination vs. embargo), transparency (named open reviews vs. blinded journal reviews), community signal (a PCI recommendation carries different weight than a journal acceptance, and the weight varies by field), and CV interpretation (search and tenure committees treat reviewed preprints inconsistently; varies by field and institution).

Journal preprint policies

Journal policies on preprints range from required to prohibited, with most journals at “permitted with conditions” in the middle. The variation matters because some authors have been desk-rejected for either preprinting (some journals consider this prior publication) or not preprinting (some funders or journals now require open-access pre-submission posting). The authoritative reference for journal-by-journal policies is SHERPA/RoMEO [14] (now JISC’s Open Policy Finder), which aggregates publisher self-disclosed policies on preprint, accepted manuscript, and published version self-archiving.

Common policy patterns:

• Preprint-friendly (most life sciences journals as of 2024): preprinting before submission is permitted with the requirement that the manuscript be appropriately cited in the published version and on the preprint server once accepted. Examples: eLife, PLOS Biology, Nature journals, Cell Press journals (with stipulations).

• Preprint-required (an emerging category): preprinting at a specified server is a precondition for submission or consideration. eLife’s post-2022 model is the clearest example; EMBO Press journals (some) accept bioRxiv-posted preprints directly for review.

• Preprint-tolerant (most clinical and applied-medicine journals as of 2024): preprinting is permitted but the journal treats it as a minor demerit in some cases, especially when the preprint received public attention before review.

• Preprint-prohibited or hostile (a shrinking but persistent category): some specialty journals, particularly in clinical surgery and some humanities subfields, treat preprinting as prior publication and decline to consider preprinted work. The list of such journals shifts; SHERPA/RoMEO is the reference.

For a venue-fit skill, the practical pattern is to check the recommended journal’s preprint policy against the author’s preprint preference and surface any incompatibility.

Funder requirements

Funder requirements have been a strong recent driver of preprint adoption. The cOAlition S “Plan S” [15] requires deposit in an open repository for funded research. NIH’s 2025 Public Access Policy [16] requires deposit of accepted manuscripts in PubMed Central upon publication. Wellcome Trust requires open access at publication, with preprint deposit accepted as compliance for some cases. Howard Hughes Medical Institute (HHMI) has been particularly strong on preprint encouragement [17].

For an automated venue-fit recommendation, funder-driven constraints are hard filters: a Wellcome-funded researcher recommended to submit to a subscription journal without an OA option is recommended to violate their funder agreement. The skill should ask about funder constraints up front when the manuscript’s financial scaffolding is non-trivial.

What the landscape says about itself: known unknowns

The preprint landscape moves faster than peer-reviewed evidence about the preprint landscape moves. Several questions are actively unresolved as of late 2024 / early 2026:

• Does preprinting affect citation rates and journal acceptance rates? Multiple studies show modest positive effects on citation [18, 19], but the cleanest causal evidence is still thin and the publication-bias confound is real.

• How do search and tenure committees weight preprints? Cross-institutional variation is large; this is a CV-strategy question without a clean answer.

• Will pre-publication review survive in fields that adopt reviewed-preprint models? eLife’s bet is that the answer is no; the broader journal ecosystem’s response is in progress.

• What is the right policy on AI-generated preprints? Several servers have begun requiring disclosure; standards are not uniform.

For an automated tool, the operational consequence is that this note should be treated as guidance to principles for recommendation, with the specifics to be verified at invocation time. The author should be pointed at SHERPA/RoMEO, DOAJ, and the specific journal’s instructions when the decision is being made, not handed an authoritative answer from training data alone.

How this informs scriptorium

For venue-fit specifically:

1. Preprints are an opt-in mode, asked once. The skill asks whether preprint recommendations are in scope before producing them. Default depends on field (life sciences and CS / physics: default ask; clinical surgery, some humanities: default ask with caveat that this is field-uncommon). When in scope, the preprint section is its own tier (not interleaved with journals); when out of scope, it’s suppressed entirely.

2. Recommend specific preprint servers, not “preprint it somewhere”. Match the server to the manuscript’s discipline (bioRxiv for life sciences, medRxiv for clinical, arXiv for physics/CS, ChemRxiv for chemistry, OSF for cross-discipline). Surface the per-server moderation rigor, license, and indexing so the author sees the trade-offs.

3. Surface the pre/post-pub review choice as a strategic decision. Within the preprint section, name PCI, Review Commons, F1000Research, and eLife’s reviewed-preprint model as the strategic alternatives to traditional review. The choice involves timing, transparency, community signal, and field convention — not a single “best” answer.

4. Check journal preprint policy against preprint recommendation. When recommending both a journal and a preprint server, verify (or caveat) that the journal accepts preprinted work from that server. Flag any incompatibility.

5. Check funder constraints. When the manuscript declares funder requirements (NIH, Wellcome, cOAlition S, etc.), filter the recommendation list against those requirements before tiering. A Wellcome paper recommended to a subscription journal without an OA option is a wrong recommendation.

6. Caveat staleness, defer to SHERPA/RoMEO at decision time. The skill names that its preprint-server and journal-policy knowledge has a date stamp and points the author at SHERPA/RoMEO for verification before submission. The verification step is part of the recommended action sequence, not an aside.

Implementation priority for scriptorium

Verdict: Direct grounding for the venue-fit skill (v0.2); preprints are an explicit mode within that skill, not a separate skill. The same-skill decision is documented in issue #82.

Why useful context anyway:

• The opt-in preprint mode pattern (default ask, then proceed) is the right shape for any decision-support feature that bridges fields with different cultural defaults. Worth being explicit about as a project-wide pattern.

• A future v0.3 preprint-policy-compliance skill, if it emerges, would consume this note’s framework. The per-journal-policy-axis content here could be extracted into a structured machine-queryable resource as a follow-up; for v0.2 it stays as a knowledge note that the skill reads.

• The fast-moving-landscape framing — “principles in this note; specifics verified at invocation time” — is the right posture for several other areas where training-data knowledge ages faster than the discipline does (the AI-agentic-scientific- writing landscape, the predatory-publishing landscape, OA policy specifics). Worth being explicit that this is a general scriptorium pattern.

Condition that would flip this: if the reviewed-preprint model (PCI, Review Commons, eLife post-2022, F1000Research) becomes the dominant publication mode in any major field, the venue-fit skill’s whole shape would shift — the question becomes “which review community / platform” rather than “which journal”. Worth re-reading this note in 18 months and updating the emphasis accordingly.

Cross-references

• venue-selection — primary grounding for venue-fit; preprint recommendation is the additional layer this note adds.
• predatory-publishing — same skill applies predatory refusal to preprint servers as well as journals (most preprint servers are not predatory in the usual sense, but the question is worth applying — the OA preprint ecosystem has predatory analogues).
• editorial-decision-making — preprint policies interact with journal triage; some editors look for preprint citation patterns in their desk-rejection heuristics.
• declared-work-scope — the convention. Preprint recommendation operates on declared work; the skill does not preprint anything on behalf of the author.

References

[1] Fraser, N., Brierley, L., Dey, G., Polka, J. K., Pálfy, M., Nanni, F., & Coates, J. A. (2021). The evolving role of preprints in the dissemination of COVID-19 research and their impact on the science communication landscape. PLoS Biology, 19(4), e3000959. DOI: 10.1371/journal.pbio.3000959. PMID: 33798194. (The canonical assessment of how COVID-19 accelerated biomedical preprinting and the implications.)

[2] Abdill, R. J., & Blekhman, R. (2019). Tracking the popularity and outcomes of all bioRxiv preprints. eLife, 8, e45133. DOI: 10.7554/eLife.45133. PMID: 31017570. (Empirical analysis of bioRxiv preprint trajectories and journal publication outcomes.)

[3] Polka, J. K., Penfold, N. C., Sever, R., Inglis, J. R., Pinto, N., & Whyte, S. (2024). State of preprinting in the life sciences. Annual Review of Biomedical Data Science. [TODO verify volume and pages; the citation is from a Polka et al. recent review of biomedical preprinting state-of-the-art. The ASAPbio website at asapbio.org has primary documentation if the formal citation needs adjustment.] (Survey of the biomedical preprint landscape.)

[4] Maggio, L. A., Artino, A. R., Picho, K., & Driessen, E. W. (2020). Are you sure you want to do that? Fostering the responsible use of preprints. Medical Education, 54(7), 631-634. DOI: 10.1111/medu.14181. PMID: 32249938. (Editorial caution about the clinical-medicine specifics of preprint risk.)

[5] arXiv. (Ongoing.) About arXiv. https://arxiv.org/about. (Primary source for arXiv submission counts, moderation policy, and history.)

[6] Cold Spring Harbor Laboratory Press. (Ongoing.) About medRxiv. https://www.medrxiv.org/about. (medRxiv screening criteria, particularly the clinical-screen layer.)

[7] Brierley, L., Nanni, F., Polka, J. K., Dey, G., Pálfy, M., Fraser, N., & Coates, J. A. (2022). Tracking changes between preprint posting and journal publication during a pandemic. PLoS Biology, 20(2), e3001285. DOI: 10.1371/journal.pbio.3001285. PMID: 35104289. (The preprint-to-published-version drift during COVID-19 — concrete evidence of preprint version-control risks.)

[8] Tay, A. (2017). The future of SSRN — bought by Elsevier in 2016. Blog post archive. [TODO verify primary documentation; the SSRN-Elsevier acquisition controversy is well-documented across scholarly-communication-Twitter from 2016-2017 but the peer-reviewed analysis is thinner.] (Documents the controversy around governance changes after the Elsevier acquisition.)

[9] Peer Community In (PCI). (Ongoing.) https://peercommunityin.org. (Community-run discipline-specific preprint recommendation system; founding paper is Casadevall & Fang 2014 on the peer-review economy, but PCI itself was founded 2016 by Dominique Bourgeon, Thomas Guillemaud, and Denis Bourguet at INRAE.)

[10] Bourguet, D., Guillemaud, T., & Bourgeon, D. (2017). Peer Community In: a recommendation process for preprints. PCI Documentation. https://peercommunityin.org. [TODO verify a formal citation for the PCI design paper; the documentation site is the primary source but a peer-reviewed account of PCI’s methodology would be the stronger reference.]

[11] Review Commons. (Ongoing.) https://reviewcommons.org. (Refereed-preprint service operated by ASAPbio and EMBO Press; the journal-independent peer-review model.)

[12] F1000Research. (Ongoing.) https://f1000research.com. (Post-publication peer-review platform operated by Taylor & Francis since 2020.) Founding paper: Tracz, V., & Lawrence, R. (2016). Towards an open science publishing platform. F1000Research, 5, 130. DOI: 10.12688/f1000research.7968.1.

[13] Eisen, M. B. (2022). Peer review without journals: A new era for eLife. eLife. [TODO verify exact citation; eLife announced the model change in October 2022 via an editorial.] The model change is documented at the eLife website and in contemporary scholarly-communication coverage.

[14] SHERPA/RoMEO (now Open Policy Finder, operated by JISC). (Ongoing.) https://openpolicyfinder.jisc.ac.uk/. (Publisher preprint and self-archiving policy database. The authoritative reference for journal-by-journal preprint policy.)

[15] cOAlition S. (Ongoing.) Plan S Principles and Implementation. https://www.coalition-s.org. (The cOAlition S funder consortium open-access requirements that drive preprint adoption among funded researchers in Europe.)

[16] National Institutes of Health (NIH). (2024). 2024 NIH Public Access Policy. https://publicaccess.nih.gov. (NIH’s 2025-effective public-access policy requiring deposit in PubMed Central upon publication.)

[17] Howard Hughes Medical Institute (HHMI). (Ongoing.) HHMI Open Access Policy. <https://www.hhmi.org/about/policies/ open-access>. (HHMI’s preprint and OA requirements; one of the most prescriptive funder-side policies.)

[18] Fu, D. Y., & Hughey, J. J. (2019). Releasing a preprint is associated with more attention and citations for the peer- reviewed article. eLife, 8, e52646. DOI: 10.7554/eLife.52646. PMID: 31808742. (Empirical evidence on preprint-citation relationship.)

[19] Wang, J., Lai, J., Yang, X., Lin, Z., Liang, S., Lin, Z., Zhao, Z., Tian, Y., Wei, X., Lin, J., & Wei, S. (2024). Effect of preprint posting on subsequent article citations: A bibliometric analysis. Journal of the Medical Library Association, 112(1), 57-66. DOI: 10.5195/jmla.2024.1684. PMID: 38486838. [TODO verify; preprint-citation effect studies are now numerous; this is a representative recent analysis. The Fu & Hughey study above is the more-cited foundational reference.]