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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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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.

145 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.
145 works in the cohort · of 4,299,418page 2 of 3

Labels cover 0 of 145 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 145 of 145 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
The golden age of DNA metasystematics
Mehrdad Hajibabaei
2012· article· en· Trends in Genetics· Environmental Science
machine prediction:candidate · noneconsensus · none
103
citations
fundno affno abstractunlabeled
Circadian rhythms
Patricia L. Lakin‐Thomas
2000· review· en· Trends in Genetics· Neuroscience
machine prediction:candidate · noneconsensus · none
100
citations
affno abstractunlabeled
Evolutionary Dynamics of Unreduced Gametes
Julia M. Kreiner, Paul Kron, Brian C. Husband
2017· review· en· Trends in Genetics· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
97
citations
affno abstractunlabeled
Adapting to environmental changes using specialized paralogs
Gabino Sanchez‐Perez, Álex Mira, Gábor Nyírő, Lejla Pašić, Francisco Rodríguez‐Valera
2008· article· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
91
citations
affno abstractunlabeled
GWA studies: rewriting the story of IBD
Marcia L. Budarf, Catherine Labbé, David Genevieve, John D. Rioux
2009· review· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
90
citations
affno abstractunlabeled
Transfer RNA gene recruitment in mitochondrial DNA
Dennis V. Lavrov, Berenice M. Lang
2005· article· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
89
citations
affno abstractunlabeled
Mouse models of cystic fibrosis
Donald J. Davidson, Mark Rolfe
2001· review· en· Trends in Genetics· Medicine
machine prediction:candidate · noneconsensus · none
84
citations
afffundno abstractunlabeled
Exploring the Alternative Splicing of Long Noncoding RNAs
Muhammad Riaz Khan, Raymund J. Wellinger, Benoît Laurent
2021· review· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
73
citations
afffundno abstractunlabeled
miRNA regulatory variation in human evolution
Jingjing Li, Zhaolei Zhang
2012· review· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
51
citations
afffundno abstractunlabeled
Introns: Good Day Junk Is Bad Day Treasure
Julie Parenteau, Sherif Abou Elela
2019· review· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
46
citations
fundno affno abstractunlabeled
At the cutting-edge of grape and wine biotechnology
Anthony R. Borneman, Simon A. Schmidt, Isak S. Pretorius
2012· review· en· Trends in Genetics· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
45
citations
affno abstractunlabeled
Throwing away DNA: programmed downsizing in somatic nuclei
Katherine H. I. Drotos, Maxim V. Zagoskin, Tony Kess, T. Ryan Gregory, Grace A. Wyngaard
2022· review· en· Trends in Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
39
citations

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