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

3,610 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.
3,610 works in the cohort · of 4,299,418page 17 of 73

Labels cover 33 of 3,610 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 3,610 of 3,610 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.

afffundno abstractunlabeled
Critical Care Cardiology Research
Sean van Diepen, Michael J. Jacka, Christopher B. Granger
2013· article· en· Circulation Cardiovascular Quality and Outcomes· Medicine
machine prediction:candidate · noneconsensus · none
11
citations
affno abstractunlabeled
Evidence-based perioperative risk reduction
W. Scott Beattie
2005· article· en· Canadian Journal of Anesthesia/Journal canadien d anesthésie· Medicine
machine prediction:candidate · noneconsensus · none
11
citations
affunlabeled
In Reply
Chelsia Gillis, Liane S. Feldman, Ann Gamsa, Francesco Carli
2015· letter· en· Anesthesiology· Medicine
machine prediction:candidate · noneconsensus · none
10
citations
aboutno affno abstractunlabeled
Canadian Cardiovascular Society
范馨月, 黄亚明
2017· article· en· Zhonghua neike zazhi· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
10
citations
affunlabeled
Quality and Outcome Assessment for Surgery
L. Chiche, Han‐Kwang Yang, Fariba Abbassi, R Robles, Steven C. Stain, Clifford Y. Ko +4 more
2023· article· en· Annals of Surgery· Medicine
machine prediction:candidate · metaresearchconsensus · none
10
citations
affunlabeled
Innovative Solutions: Leading the Way
Mary Lu Daly, J. Patrick Powers, Vicky Orto, Marlene Rogers, Tina Dickinson, Michele Fabris +1 more
2006· article· en· Dimensions of Critical Care Nursing· Medicine
machine prediction:candidate · noneconsensus · none
10
citations
aboutno affunlabeled
The Perioperative Surgical Home
Thomas R. Vetter, Jean‐François Pittet
2015· letter· en· Anesthesia & Analgesia· Medicine
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Volitional Delay of Self-Reported Outcomes
Alexander Villafranca, Benjamin G. Arenson, Michael S. Avidan, David B. Glick, George A. Mashour, Eric Jacobsohn
2013· article· en· Anesthesia & Analgesia· Medicine
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
The Surgical Apgar Score
Elliot Pittman, Elijah Dixon, Kaylene Duttchen
2022· review· en· Annals of Surgery Open· Medicine
machine prediction:candidate · noneconsensus · none
10
citations

How this was built: Screen · Findings · About