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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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Telemedicine and Telehealth Implementation
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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.

2,877 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.
2,877 works in the cohort · of 4,299,418page 27 of 58

Labels cover 17 of 2,877 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 2,877 of 2,877 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.

afffundunlabeled
Virtual care in community pharmacy services: a scoping review
Yasmin H. Aboelzahab, Andrea McCracken, Reema Abdoulrezzak, Sarah Naguib, Marcia McLean, Andrea C. Tricco +2 more
2025· review· en· Research in Social and Administrative Pharmacy· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
affaboutunlabeled
Lessons Learned From Telehealth Pioneers
Ann Frantz, Jane Colgan, Krisan Palmer, Bonita Ledgerwood
2002· article· en· Home Healthcare Nurse· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
venueno affgemma · bibliometricsgpt · bibliometricsmodels split
Chinese Health Insurance in the Digital Era: Bibliometric Study
Zhiyuan Hu, Xiaoping Qin, Chen Kai-yan, Yu-Ni Huang, Richard S. Wang, Tao‐Hsin Tung +2 more
2024· article· en· Interactive Journal of Medical Research· Medicine
machine prediction:candidate · bibliometricsconsensus · none
5
citations
afffundaboutunlabeled
Patient and Physician Assessments of Clinical Status
Amanda Grant-Orser, N.A. Adderley, Katelyn Stuart, Charlene D. Fell, Kerri A. Johannson
2023· article· en· CHEST Pulmonary· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
affvenueaboutunlabeled
A Systems-Level Evaluation Framework for Virtual Care
Meaghan Lunney, Mary V. Modayil, Judith Krajnak, Katie Woo, Shy Amlani, Kris Gray +4 more
2023· article· en· Healthcare Quarterly· Medicine
machine prediction:candidate · metaresearchconsensus · none
4
citations

How this was built: Screen · Findings · About