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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.

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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.

589 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.
589 works in the cohort · of 4,299,418page 9 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.

aboutno affunlabeled
PP44 Optimal Use Of Warfarin: Self-Monitoring From A Quebec Perspective
Sylvie Bouchard, Frederic St-Pierre, Ann Lévesque, Mélanie Turgeon, Hélène Guay, Adriana Freitas +3 more
2019· article· en· International Journal of Technology Assessment in Health Care· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP68 Indicators From The Real World Data To Improve Opioid Use
Éric Tremblay, Jean-Marc Daigle, Marie-Claude Breton, Sylvie Bouchard
2019· article· en· International Journal of Technology Assessment in Health Care· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP17 Comprehensive Evaluation Of A Technology With Expanding Indications
Laurie Lambert, François Désy, L. Azzi, Maria Vutcovici, Anabèle Brière, Lucy J. Boothroyd +3 more
2018· article· en· International Journal of Technology Assessment in Health Care· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP04 Co-Constructing Recommendations With Patients And Health Professionals
Laurie Lambert, Lucy J. Boothroyd, L. Azzi, Caroline Collette, Philippe Brouillard, Marie‐Pascale Pomey +6 more
2018· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP39 Health Technology Assessment And Aging: Moving Evidence To Action
Heather McNeil, Don Juzwishin, Paul Stolee, Jeonghoon Ahn, Yingyao Chen, Americo Cicchetti +1 more
2018· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
VP189 Hemolysis Induced By Modern Infusion Pumps During Blood Transfusion
Thomas G. Poder, Jean-Christian Boileau, Renée Lafrenière, Louis Thibault, Nathalie Carrier, Marie-Joëlle de Grandmont +1 more
2017· article· en· International Journal of Technology Assessment in Health Care· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP193 How Does HTA Address Social Expectations Now? An International Survey.
Hubert Gagnon, Christian Bellemare, Georges-Auguste Legault, Suzanne K. Bédard, Jean-Pierre Béland, Louise Bernier +5 more
2019· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP43 Impact Of The COVID-19 Pandemic In The Brazilian National Committee for Health Technology Incorporation (Conitec) Recommendation Process
Marília Mastrocolla de Almeida Cardoso, Lehana Thabane, Juliana Rugolo, Daniel Da Silva Pereira Curado, Luis Gustavo Modelli, Silvana Andréa Molina Lima +1 more
2022· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Adaptive Evolution in Rapid Assessments: A 25-Year Perspective
Paula Corabian, Bing Guo, Carmen Moga, N. Ann Scott
2019· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
PP34 A Cost-Utility Analysis Of The Syncope: Pacing Or Recording Trial
Mark Hofmeister, Robert S. Sheldon, Eldon Spackman, Satish R. Raj, Mario Talajic, Giuliano Becker +8 more
2018· article· en· International Journal of Technology Assessment in Health Care· Medicine
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About