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Paste your working title and abstract and see which journals published the papers closest to yours. The finder searches trusted open scientific databases, aggregates the venues behind the closest matches, and returns a shortlist with citation metrics, open access status and article processing charges. No AI model is involved, so nothing in the results can be invented.
0 words (at least 30 needed for a reliable match)
Trusted by researchers publishing in
A draft is fine. The closer the text is to your real abstract, with your field's terminology, the method and the population, the sharper the match. At least 30 words are needed for a reliable signal.
Your abstract is searched against open indexes covering hundreds of millions of papers, and the finder looks at where the closest matches were actually published. Journals that keep appearing among those papers rise to the top.
Each candidate shows the matching articles as evidence, plus citation metrics, open access status, DOAJ listing and the reported processing charge. Open the matches, check the journal's scope, then decide.
Every recommendation exists because real papers close to yours were published there, and those papers are shown on the card. You are not trusting a black box; you can read the evidence yourself.
The 2-year citation average, h-index and article counts come from trusted open scientific databases, so you can compare candidates on the same footing instead of hunting numbers across publisher sites.
Open access status, DOAJ listing and reported article processing charges sit on every card, with a one-click filter for open access venues, so funding requirements are checked before you fall for a journal.
The search runs in your browser and queries the public database APIs directly, with no middle layer rewriting the results, so what you see is what the indexes hold at that moment.
Picking the wrong journal is the most expensive mistake in academic publishing, and the most common. A desk reject for scope costs weeks; a submission to a questionable venue can cost the paper itself. Yet the way most researchers choose, from a colleague's suggestion or a publisher's own matching widget, either samples one person's reading or searches one publisher's catalogue. The question that actually predicts fit is simpler: where do papers like this one get published?
That is the question this finder answers literally. It searches trusted open scientific databases for the papers closest to your title and abstract, then aggregates the journals behind them. A journal that published several of your nearest neighbors is, almost by definition, a venue whose editors and reviewers read work like yours. Because the whole process is retrieval and counting, with no AI model anywhere, the results cannot contain an invented journal, an invented metric or an invented match: every card links to the real papers that put it there.
The metrics deserve one honest note. The 2-year citation average shown on each card is built the same way as the familiar impact factor, but from open citation data, so the values will not equal the proprietary figures and are best used to compare the journals in your list against each other. The open access and DOAJ labels carry different weight: DOAJ listing means the journal passed an independent vetting process, which is one of the more reliable quick checks against predatory venues. And the reported article processing charge is exactly that, reported; confirm it on the publisher's page, where waivers and discounts also live.
Once the target is chosen, the rest of the pre-submission checklist is writing quality and reference integrity. The citation finder fills evidence gaps in your argument, the AI citation checker verifies the final reference list against the same open databases, and our hallucinated-citation audit covers the manual checks editors increasingly expect.
No AI model is involved anywhere in this tool. Retrieval and counting over open scholarly data, nothing else.
Recommendations come from where the papers closest to your abstract were actually published, not from a directory lookup or a model's opinion. Each journal card shows you those matching papers, so the evidence for every recommendation is one click away.
Every journal is a real indexed publication venue, and the citation average, h-index, open access status and processing charge are read verbatim from trusted open scientific databases. Nothing in a result is generated.
The search runs in your browser and queries the public database APIs directly, the same way a search box on their own sites would, so the shortlist reflects exactly what the indexes hold.
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