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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
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.

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 12 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.

affno abstractunlabeled
Guidelines to the Practice of Anesthesia - Revised Edition 2014
Richard N. Merchant, Daniel Chartrand, Steven Dain, Gregory Dobson, Matt M. Kurrek, Annie Lagacé +2 more
2014· article· en· Canadian Journal of Anesthesia/Journal canadien d anesthésie· Medicine
machine prediction:candidate · noneconsensus · none
21
citations
afffundno abstractunlabeled
Office-based anesthesia
Matt M. Kurrek, Rebecca S. Twersky
2010· review· en· Canadian Journal of Anesthesia/Journal canadien d anesthésie· Medicine
machine prediction:candidate · noneconsensus · none
21
citations
affgemma · no categorygpt · no categorymodels split
The Wessex Fit-4-Cancer Surgery Trial (WesFit): a protocol for a factorial-design, pragmatic randomised-controlled trial investigating the effects of a multi-modal prehabilitation programme in patients undergoing elective major intra–cavity cancer surgery
Malcolm West, Andrew Bates, Chloe Grimmett, Cait Allen, Richard Green, Lesley Hawkins +10 more
2021· preprint· en· F1000Research· Medicine
machine prediction:candidate · noneconsensus · none
20
citations
affvenueunlabeled
Technical innovations that may facilitate real-time telementoring of damage control surgery in austere environments: a proof of concept comparative evaluation of the importance of surgical experience, telepresence, gravity and mentoring in the conduct of damage control laparotomies
Andrew W. Kirkpatrick, Anthony J. LaPorta, Susan Brien, Tim Leslie, Elon Glassberg, Jessica McKee +5 more
2015· article· en· Canadian Journal of Surgery· Medicine
machine prediction:candidate · noneconsensus · none
20
citations
affvenueno abstractunlabeled
Perioperative Optimization of the Cardiac Surgical Patient
Alexander J. Gregory, Christopher Noss, Rosaleen Chun, Michael Gysel, Christopher Prusinkiewicz, Nicole M. Webb +7 more
2023· review· en· Canadian Journal of Cardiology· Medicine
machine prediction:candidate · noneconsensus · none
20
citations
aboutno affunlabeled
Machine Learning Comes of Age
Michael Burns, Sachin Kheterpal
2020· editorial· en· Anesthesiology· Medicine
machine prediction:candidate · noneconsensus · none
19
citations
affunlabeled
Intraoperative cardiac arrest
Fei Han, Yufeng Wang, Yue Wang, Jiaxu Dong, Chaoran Nie, Meng Chen +1 more
2017· article· en· Medicine· Medicine
machine prediction:candidate · noneconsensus · none
19
citations

How this was built: Screen · Findings · About