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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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Canadian Journal of Ophthalmology
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Retraction
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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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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.

4,046 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.
4,046 works in the cohort · of 4,299,418page 19 of 81

Labels cover 8 of 4,046 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 4,046 of 4,046 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.

venueno affno abstractunlabeled
Cavitary choroidal melanoma
Emiliano M. Becerra, María A. Saornil, Gonzalo Blanco, María Méndez, Yerena Muiños, María R. Esteban
2005· article· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
14
citations
venueno affno abstractunlabeled
Diabetes as a possible predisposer for blepharitis
Hasan Ghasemi, Reza Gharebaghi, Fatemeh Heidary
2008· letter· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
14
citations
affvenueno abstractunlabeled
Comparison of ophthalmic training in 6 English-speaking countries
Abigail T. Fahim, Matthew P. Simunovic, Zaid Mammo, Danny Mitry, Kaivon Pakzad-Vaezi, Patrick D. Bradley +1 more
2016· article· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
14
citations
venueno affno abstractunlabeled
Mapping choroidal thickness in patients with type 2 diabetes
Beatriz Abadía, Francisco de Asís Bartol-Puyal, Pilar Calvo, Guayente Verdes, Carlos Isanta, Luís E. Pablo
2019· article· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
14
citations
affvenueaboutno abstractunlabeled
The Toronto epidemiology glaucoma survey: a pilot study
Ayako Anraku, Ya-Ping Jin, Ziad Butty, Delan Jinapriya, Tariq Alasbali, Zaid Mammo +2 more
2011· article· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
14
citations
venueno affno abstractunlabeled
Novel imaging modalities in patients with uveitis
Gábor Deák, Mei Zhou, Anna Sporysheva, Debra A. Goldstein
2019· review· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
14
citations
venueno affno abstractunlabeled
Ocular effects of criminal drug use
Alison Firth
2006· editorial· en· Canadian Journal of Ophthalmology· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
14
citations

How this was built: Screen · Findings · About