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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.

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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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Genetic and phenotypic traits in livestock
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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.

2,937 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.
2,937 works in the cohort · of 4,299,418page 34 of 59

Labels cover 5 of 2,937 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 2,937 of 2,937 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.

afffundno abstractunlabeled
Representing genomic structural variation
Cydney Nielsen, Bang Wong
2012· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
Assessing the accuracy of imputation in the Gyr breed using different SNP panels
Alejandra Maria Toro Ospina, Ignácio Aguilar, Matheus Henrique Vargas de Oliveira, Luiz Eduardo Cruz dos Santos Correia, Aníbal Eugênio Vercesi Filho, Lúcia Galvão de Albuquerque +1 more
2021· article· en· Genome· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
afffundaboutunlabeled
Selection signatures in Gir and Holstein cattle
Larissa G Braga, Flávio S. Schenkel, T.C.S. Chud, Júlia L Rodrigues, Bacem Saada, Marco Antônio Machado +3 more
2025· article· en· Journal of Dairy Science· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
A terminal-sire index for selecting rams
J. J. Tosh, J. W. Wilton
2002· article· en· Canadian Journal of Animal Science· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Congenital abnormalities of the cervix in mares
Catherine M. Card
2012· article· en· Equine Veterinary Education· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
DAIRY ANIMALS | Sheep Breeds
M. H. Fahmy, J.N.B. Shrestha
2002· book-chapter· en· Encyclopedia of Dairy Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Modifying MACE to accommodate genomic preselection effects
P G Sullivan, Esa Mäntysaari, Gerben DeJong, Haïfa Benhajali
2019· article· en· Jukuri (Luonnonvarakeskus Tietopalvelu)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaresearchconsensus · none
3
citations
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How this was built: Screen · Findings · About