Why are we doing this?
We believe in transparency. Understanding how Keenious works helps you trust the results, steer the process, and notice why results might differ from what you expected.
What Keenious considers
Keenious builds an understanding of your information need from:
The words you type (prompts and follow-ups)
Whatâs currently displayed in the content frame (a paper or result list)
Any text you highlight
Uploaded PDFs (within size limits)
If your prompt is brief (e.g., âshow me research on climate changeâ), our language model expands it to add helpful context so a meaningful search can run. You can always edit the query, add or remove filters, or take over completely.
The key factors that influence ranking
1) Semantic understanding of your request
Keenious interprets the meaning of what youâre asking (including entities and methodologies) to find papers truly about your subjectâeven if phrasing differs or the paper is in another language. This reduces missed-but-relevant results when wording varies.
2) Exact-term requirements (only when you say so)
If you explicitly state that certain terms must appear (e.g., âpapers must mention PyMOLâ), Keenious adds a precise term-matching clause to ensure those terms are present. Otherwise, strict term requirements are avoided so you donât miss relevant papers that use alternate wording.
Balance: Papers that are strong on both semantic relevance and (when requested) exact-term evidence tend to rank higher.
3) Citation count
Citations provide a signal of visibility/influence. Helpful but imperfect: older papers naturally accumulate more citations, and practices vary by field.
4) Recency of publication
Newer work receives a gentle boost so current research is easier to findâwithout hiding foundational studies.
Additional practical signals
Abstract availability: Papers with abstracts are favored so you can assess relevance faster.
âFormat/DOI emphasis: Articles and reviews with DOIs get a boost; if strong matches are scarce, other work types from OpenAlex are included so useful material still appears.
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Boosts vs. filters (you stay in control)
No automatic restrictive filters are applied. Instead, boosts influence ordering without hiding results.
Only automatic exclusion: retracted items are filtered out.
Everything elseâyears, document type, open access, languageâis up to you and clearly adjustable in the interface.
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Data fidelity & duplicates
Keenious mirrors OpenAlex faithfully. OpenAlex handles most versioning and de-duplication, but occasional duplicates can appear. We donât rewrite or merge source records.
Personalization & privacy
Thereâs no personalization of ranking today. Any future experiments will be transparent and optional (opt-out available).
In summary
Keenious performs searches based on your input, gathers candidates through semantic understanding (and exact-term requirements when you request them), and ranks with a balanced blend of meaning, evidence, recency, and practical signals like abstractsâwhile filtering out only retractions. You retain full control at every step.