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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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Influenza Virus Research Studies
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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.

3,839 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.
3,839 works in the cohort · of 4,299,418page 33 of 77

Labels cover 16 of 3,839 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 3,839 of 3,839 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
Introductory paper: High-dose influenza vaccine
Mia Diaco, Lee-Jah Chang, Bruce T. Seet, Corey Robertson, Ayman Chit, Monica Mercer +3 more
2021· editorial· en· Vaccine· Medicine
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
Pertussis models to inform vaccine policy
Patricia T. Campbell, James M. McCaw, Jodie McVernon
2015· review· en· Human Vaccines & Immunotherapeutics· Medicine
machine prediction:candidate · noneconsensus · none
15
citations
venueno affunlabeled
Pandemic Influenza A (H1N1) and Its Prevention: A Cross Sectional Study on Patients’ Knowledge, Attitude and Practice among l study on Patients’ Knowledge, Attitude and Practice among patients attending Primary Health Care Clinic in Kuala Lumpur, Malaysia
Latiffah Abdul Latiff, Saadat Parhizkar, Huda Zainuddin, Goh M Chun, Mohammad Ali A Rahiman, Nur Liyana N Ramli +1 more
2012· article· en· Global Journal of Health Science· Medicine
machine prediction:candidate · noneconsensus · none
15
citations
afffundaboutunlabeled
Vaccine Effectiveness of non-adjuvanted and adjuvanted trivalent inactivated influenza vaccines in the prevention of influenza-related hospitalization in older adults: A pooled analysis from the Serious Outcomes Surveillance (SOS) Network of the Canadian Immunization Research Network (CIRN)
Henrique Pott, Melissa K. Andrew, Zachary Shaffelburg, Michaela Nichols, Lingyun Ye, May ElSherif +22 more
2023· article· en· Vaccine· Medicine
machine prediction:candidate · noneconsensus · none
15
citations
venueno affno abstractunlabeled
Pandemic 2009 influenza A H1N1 retinopathy
Omar Faridi, Tushar M. Ranchod, Lawrence Y. Ho, Alan Ruby
2010· letter· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Influenza in Pregnancy: The Case for Prevention
Shelly McNeil, Beth Halperin, Noni E. MacDonald
2008· article· en· Advances in experimental medicine and biology· Medicine
machine prediction:candidate · noneconsensus · none
15
citations

How this was built: Screen · Findings · About