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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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Transplantation: Methods and Outcomes
Retraction
Abstract
Evidence source
Study design
Label agreement
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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
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venuejournal
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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.

2,706 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
2,706 works in the cohort · of 4,299,418page 50 of 55

Labels cover 6 of 2,706 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 2,706 of 2,706 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.

affno abstractunlabeled
Reply to the Editor
Marc de Perrot, Shaf Keshavjee
2007· article· en· Journal of Thoracic and Cardiovascular Surgery· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/j.ysur.2016.03.117
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Hemodynamics and ECMO
2025· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1241-8226(17)68679-1
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Pflegerische Aspekte nach Herztransplantation
Hans H. Scheld, Dieter Hammel, Mario C. Deng, Çhristof Schmid
2001· book-chapter· de· Steinkopff eBooks· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
193
Marcelo Cantarovich, Nadia Giannetti, Gaëlle Fontaine, R. Chartier, E. Cyr, Renzo Cecere
2006· article· en· The Journal of Heart and Lung Transplantation· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Posttransplant heart failure
Philip T. Thrush, Simon Urschel, Elfriede Pahl
2025· book-chapter· en· Elsevier eBooks· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
361
Adil Al Riyami, Mann Chandavimol, C. Imai, Lynn Straatman, A. Kaan, Andrew Ignaszewski
2006· article· en· The Journal of Heart and Lung Transplantation· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
341: Proteomic Biomarkers of Chronic Heart Allograft Rejection
Gabriela V. Cohen Freue, David Lin, C. Imai, Andrew Ignaszewski, Julien Mancini, Zsuzsanna Hollander +9 more
2009· article· en· The Journal of Heart and Lung Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About