For authors

If you write your papers in markdown — or are willing to — PABC is built for you. Here is the case for choosing PABC, how to prepare a submission, and how review works once you submit.

Why publish with PABC

• It's open access and cheap. Under $1000, and everyone can read your work.
• You keep the copyright. Publication is under an open license.
• No formatting busywork. Write in markdown; we do the typesetting.
• We fix trivia ourselves. Small style corrections are made for you, not bounced back.
• Reviewers actually read a readable paper, so their feedback is better.
• Guaranteed publication for sound science. Review decides your tier, not whether you're in.
• No rejection-and-resubmission treadmill. Reviewed once, published once.

We do not push our work onto you

There is a habit in academic publishing of returning a manuscript over trivia — strip the ZIP codes out of the affiliations, change that dagger to an asterisk — costing the author a round trip through the entire submission system to perform a minute of data entry. PABC treats that as a bug to fix, not a policy to enforce:

• If a change is small, mechanical, and unambiguous, we make it. Style normalization of affiliations, symbols, reference formatting, and similar trivia are handled automatically.
• Every automatic change is shown to you. Corrections are itemized; you can reject any of it.
• We only send something back when it genuinely needs your judgment — a missing figure, an unresolvable reference, a claim the cited source does not support.

If you need to submit a Word document, PABC is not the right venue.

Preparing your manuscript

PABC accepts manuscripts in markdown. There are no formatting requirements at submission beyond a well-formed source.

What you provide

• Your manuscript body in markdown, with pandoc-style citation keys ([@smith2020])
• Figures as image files, referenced from the markdown
• A bibliography as BibTeX or CSL-JSON — whatever your reference manager already exports
• Author and affiliation metadata, entered once in the byline editor

You can hand us a link-shared Google Drive folder containing all of the above and we will sort out which file is which, or upload the files directly.

What you do not do

• No journal template to fill in
• No re-typesetting figures or tables
• No wrestling with a submission-system formatter
• No house-style data entry. Small mechanical corrections are made for you and shown to you.

What we check automatically

The moment you submit, an automated battery runs and reports back within minutes: figure resolution and legibility, figure citation order, reference resolution against Crossref and OpenAlex, whether cited sources actually support the claims made about them, and text-overlap screening. You see the results before a reviewer does. From your single markdown source, PABC then generates the typeset web article and a printable page-based version automatically; you'll see and approve a proof before publication.

The submission process

The pipeline runs on HydraPub. From the author's side it is deliberately short.

1. Submit. Upload your markdown manuscript and metadata. Choose your track.
2. Review. Reviewers read the typeset paper and provide feedback in place.
3. Revise. Respond to reviewer comments and submit a revision.
4. Decision and tiering. Editors record a decision and the paper is placed into its tier.
5. Proof. You review and approve the final typeset proof.
6. Publish. The article goes live with a DOI, open license, and is queued for indexing.

We have no real timing data yet — nothing has been published — but the design targets are worth stating: automated checks within minutes of submission, reviewers self-selected in days rather than weeks, reviews back in weeks rather than months, a decision in days once reviews are in, and proof-to-publication in days because production is automatic. The savings come from the queues, not from rushing the reading.

How review works

Peer review is the hardest cost to cut without destroying quality, so PABC redesigns it rather than skips it. Review is really two problems, and journals usually only try to solve the first:

Finding reviewers

Academy members carry an annual reviewing assignment — reviewing is a condition of membership — so the months traditionally spent cold-emailing strangers simply do not happen. Submissions are posted to an internal queue where reviewers self-select the papers matching their interests, closer to how Stack Overflow contributors pick questions than to an editor guessing who might fit. Editors can still invite a specific person when a submission needs expertise the pool does not cover. Review service earns points and a visible, citable record.

The review process itself

Reviewers receive the paper as it would be published: properly typeset, figures in place, references resolved — not a double-spaced document with the figures in an appendix. Feedback is left directly on the passage it concerns, the way you would comment in a Google Doc, rather than compiled into a numbered list and emailed back. Before a human opens the paper, the automated checks have run and the AI reviewers have filed their reports. Better tooling produces better reviews, which are less miserable to write — so reviewers are more willing to review again, which keeps the pool healthy and review fast.

AI reviews, and what they are for

AI does write substantive reviews at PABC. What it does not do is render judgment: it never assigns a tier, never recommends accept or reject, and never counts toward a decision or a quorum. The distinction is enforced in the software — an AI review is structurally incapable of carrying a verdict, and the code that computes quorum and tier placement reads only human reviews.

The AI reviewers, each with a distinct remit:

• Novelty — works out what the paper claims, then searches the literature for the nearest prior art. Held to what it actually retrieved: a citation outside the retrieved set is rejected mechanically, so it cannot invent prior art.
• Rigor — reproducibility and internal consistency. Are methods described well enough to repeat? Are data and code available? Do the numbers agree?
• Clarity — structure, undefined terms, figure legibility, and claims that outrun the evidence.
• Generalist — an overall read of the manuscript.

This frees the human reviewer to spend their attention on what only they can supply: whether the question matters, whether the approach is sound, whether the conclusions follow, and where the paper belongs. That judgment is the part AI is kept away from. Under the proposed tier model, reviewers decide where a paper belongs rather than merely whether to accept it.