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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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Disaster Response and Management
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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.

1,873 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.
1,873 works in the cohort · of 4,299,418page 7 of 38

Labels cover 10 of 1,873 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 1,873 of 1,873 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
Nursing Students’ Perceived Disaster Preparedness and Response
Joy Kabasindi Kamanyire, Ronald Wesonga, Susan Achora, Anju Malik, Sultan Al‐Shaqsi, Jamila AS Alhabsi
2021· article· en· Sultan Qaboos University medical journal· Health Professions
machine prediction:candidate · noneconsensus · none
19
citations
affno abstractunlabeled
Anesthesia Implications of Blast Injury
Kay B. Leissner, Rafael Ortega, W. Scott Beattie
2006· review· en· Journal of Cardiothoracic and Vascular Anesthesia· Health Professions
machine prediction:candidate · noneconsensus · none
19
citations
affno abstractunlabeled
Finite Element Modeling for the Prediction of Blast Trauma
Alexander Greer, Duane S. Cronin, Chris Salisbury, Kevin Williams
2005· book-chapter· en· Solid mechanics and its applications· Health Professions
machine prediction:candidate · noneconsensus · none
19
citations
affvenueno abstractunlabeled
Ensuring a Broad and Inclusive Approach
Rodney Kort, Allison J. Stuart, Erika Bontovics
2005· article· en· Canadian Journal of Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
18
citations
affvenueno abstractunlabeled
Responding to Pandemic Influenza
Laurie A. Doxtator, Charles Gardner, Jennifer Medves
2004· article· en· Canadian Journal of Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
18
citations
affunlabeled
Patients for Patient Safety
Susan E. Sheridan, Heather Sherman, Allison Kooijman, E. Bermudez Vazquez, Katrine Kirk, Nagwa Metwally +1 more
2020· book-chapter· en· Health Professions
machine prediction:candidate · noneconsensus · none
17
citations
afffundno abstractunlabeled
Pandemic risk management using engineering safety principles
Mohammad Alauddin, Faisal Khan, Syed Imtiaz, Salim Ahmed, Paul Amyotte
2021· article· en· Process Safety and Environmental Protection· Health Professions
machine prediction:candidate · noneconsensus · none
17
citations
aboutno affunlabeled
Global Emergency Medicine: A Review of the Literature From 2012
Gabrielle A. Jacquet, Mark Foran, Susan A. Bartels, Torben K. Becker, Erika D. Schroeder, Herbert C. Duber +3 more
2013· review· en· Academic Emergency Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
Caring for Critically Ill Patients in Humanitarian Settings
James Lee, Simon W. P. Roberts, Kanya Götsch, Ulrike Moeller, Laura Hawryluck
2018· article· en· American Journal of Respiratory and Critical Care Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
16
citations

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