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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Meta-analysis and systematic reviews
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

4,076 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
4,076 works in the cohort · of 4,299,418page 34 of 82

Labels cover 359 of 4,076 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 4,076 of 4,076 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affvenueunlabeled
Covidence and Rayyan
Rachel Couban
2016· article· en· Journal of the Canadian Health Libraries Association / Journal de l Association de bilbiothèques de la santé du Canada· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
16
citations
affunlabeled
Cochrane Reviews: new blocks on the kids
Ian Shrier
2003· article· en· British Journal of Sports Medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
16
citations
affunlabeled
Addressing the Unit of Analysis in Medical Care Studies
Aaron W. Calhoun, Gordon Guyatt, Michael D. Cabana, Downing Lu, David A. Turner, Stacey L. Valentine +1 more
2008· review· en· Medical Care· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
16
citations
aboutno affunlabeled
The Most Commonly Cited Articles in Pediatric Surgical Journals
Sinan Celayir, Serdar Sander, Mehmet Eliçevik, Alperen Vural, Ayşenur Cerrah Celayir
2008· article· en· European Journal of Pediatric Surgery· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
16
citations
affunlabeled
A Causal Inference Approach to Network Meta-Analysis
Mireille E. Schnitzer, Russell Steele, Michèle Bally
2016· article· en· RePEc: Research Papers in Economics· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
16
citations
affunlabeled
Improving the Science in Plastic Surgery
Jessica Murphy, Sophocles H. Voineskos, Christopher J. Coroneos, Charles H. Goldsmith
2022· article· en· Plastic & Reconstructive Surgery· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
15
citations
affgemma · metaresearch+metaepi_broadgpt · metaresearch+metaepi_narrow+metaepi_broadmodels split
Quantifying the impact of immortal time bias: empirical evidence from meta-analyses
Min Seo Kim, Dong Keon Yon, Seung Won Lee, Masoud Rahmati, Marco Solmi, André F. Carvalho +4 more
2025· article· en· Journal of the Royal Society of Medicine· Decision Sciences
machine prediction:candidate · metaresearch+metaepi_broadconsensus · metaresearch
15
citations
affno abstractgemma · metaresearchgpt · metaresearchmodels agree
Benign and malignant scientific irreproducibility
Clare Fiala, Eleftherios P. Diamandis
2018· editorial· en· Clinical Biochemistry· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
15
citations

How this was built: Screen · Findings · About