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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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Reliability and Agreement in Measurement
Retraction
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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.

affaffiliation
fundfunder
venuejournal
aboutaboutness

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

305 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
305 works in the cohort · of 4,299,418page 3 of 7

Labels cover 3 of 305 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 305 of 305 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.

affunlabeled
Assessing the quality of evidence in studies estimating prevalence of exposure to occupational risk factors: The QoE-SPEO approach applied in the systematic reviews from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury
Frank Pega, Natalie C. Momen, Diana Gagliardi, Lisa Bero, Fabio Boccuni, Nicholas Chartres +16 more
2022· article· en· Environment International· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
12
citations
affno abstractunlabeled
Assessing the performance of diagnostic test accuracy measures
Sofia Tsokani, Areti Angeliki Veroniki, Nikolaos Pandis, Dimitris Mavridis
2022· editorial· en· American Journal of Orthodontics and Dentofacial Orthopedics· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
8
citations
affno abstractunlabeled
Ordinal Alpha
Anne Gadermann, Martin Guhn, Bruno D. Zumbo
2014· book-chapter· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
7
citations
affvenueaboutunlabeled
Planning and analysis of measurement reliability studies
Stefan Steiner, Nathaniel T. Stevens, Ryan P. Browne, Robert J. MacKay
2011· article· en· Canadian Journal of Statistics· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
6
citations
affunlabeled
Agreement Between Two Ratings with Different Ordinal Scales
S. Natarajan, M. Brent McHenry, Stuart R. Lipsitz, Neil Klar, Steven E. Lipshultz
2007· book-chapter· en· Birkhäuser Boston eBooks· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
5
citations
affunlabeled
Reliability
David L. Streiner, Geoffrey R. Norman, John Cairney
2014· book· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Bias, Overview
Bernard C. K. Choi, Anita W. P. Pak
2005· other· en· Encyclopedia of Biostatistics· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
4
citations
affvenueunlabeled
Correction
Edward J. Mills
2005· article· en· Canadian Medical Association Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Agreement, Measurement of
M. M. Shoukri
2014· other· en· Wiley StatsRef: Statistics Reference Online· Decision Sciences
machine prediction:candidate · noneconsensus · none
3
citations

How this was built: Screen · Findings · About