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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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International Journal of Technology Assessment in Health Care
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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.

589 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
589 works in the cohort · of 4,299,418page 7 of 12

Labels cover 3 of 589 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 589 of 589 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
Demonstrating the influence of HTA: INAHTA member stories of HTA impact
Sophie Werkö, Tracy Merlin, Laurie Lambert, Paul Fennessy, Ana Pérez Galán, Tara Schuller
2020· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affaboutunlabeled
MEDICAL DEVICE RECALLS IN CANADA FROM 2005 TO 2015
Anna R. Gagliardi, Julie Takata, Ariel Ducey, Pascale Lehoux, Sue Ross, Patricia Trbovich +3 more
2017· article· en· International Journal of Technology Assessment in Health Care· Health Professions
machine prediction:candidate · noneconsensus · none
6
citations
affaboutunlabeled
USING THE INTEGRATE-HTA GUIDANCE: EXPERIENCE FROM CADTH
Kenneth Bond, Laura Weeks
2017· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
6
citations
affunlabeled
HTAI POLICY FORUM: KEEPING HTA ON TRACK
Carole Longson
2014· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
HOSPITAL-BASED HEALTH TECHNOLOGY ASSESSMENT IN IRAN
Farideh Mohtasham, Reza Majdzadeh, Ensiyeh Jamshidi
2017· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
5
citations
affaboutunlabeled
MEDICAL DEVICE PRICES IN ECONOMIC EVALUATIONS
İlke Akpinar, Philip Jacobs, Don Husereau
2015· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
5
citations
affaboutunlabeled
INTRODUCTION: PRACTICE GUIDELINES
J. Jaime
2000· article· en· International Journal of Technology Assessment in Health Care· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
aboutno affunlabeled
PP115 A Mobile Health App To Improve Knee Osteoarthritis Self-Management
Deborah A. Marshall, Tanya Barber, Brittany Shewchuk, Kelly Mrklas, Jean Miller, Sylvia Teare +4 more
2018· article· en· International Journal of Technology Assessment in Health Care· Health Professions
machine prediction:candidate · noneconsensus · none
4
citations
affaboutunlabeled
Impact of rarity on Canadian oncology health technology assessment and funding
James Keech, Wei Fang Dai, Maureen Trudeau, Rebecca E. Mercer, Rohini Naipaul, Frances C. Wright +7 more
2020· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
4
citations
affgemma · no categorygpt · no categorymodels split
LIFETIME COSTS FOR MEDICAL SERVICES: A METHODOLOGICAL REVIEW
Philip Jacobs, Kamran Golmohammadi, Teresa Longobardi
2003· review· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
4
citations
fundno affunlabeled
HTA capacity building in Asia: towards one goal
Linda M. Mundy, Guy J. Maddern
2023· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations

How this was built: Screen · Findings · About