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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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Trends in Biochemical Sciences
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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.

110 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.
110 works in the cohort · of 4,299,418page 2 of 3

Labels cover 1 of 110 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 110 of 110 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
Do Mammalian Cells Really Need to Export and Import Heme?
Prem Ponka, Alex D. Sheftel, D. Scott Bohle, Daniel Garcia‐Santos
2017· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
73
citations
fundno affno abstractunlabeled
A Cap for Every Occasion: Alternative eIF4F Complexes
J.J.David Ho, Stephen Lee
2016· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
52
citations
afffundno abstractunlabeled
Pre-mRNA splicing: a complex picture in higher definition
Matthew J. Schellenberg, Dustin B. Ritchie, Andrew M. MacMillan
2008· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
50
citations
afffundno abstractunlabeled
Molecular determinants of protein evolvability
Karol Buda, C.M. Miton, Xingyu Cara Fan, Nobuhiko Tokuriki
2023· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
36
citations
afffundno abstractunlabeled
SRC homology 3 domains: multifaceted binding modules
Ugo Dionne, Lily J Percival, François Chartier, Christian R. Landry, Nicolas Bisson
2022· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
33
citations
afffundno abstractunlabeled
Many Light Touches Convey the Message
James W. Dennis
2015· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
32
citations
afffundno abstractunlabeled
Limiting the DNA Double-Strand Break Resectosome for Genome Protection
Daryl A. Ronato, Sofiane Y. Mersaoui, Franciele Faccio Busatto, El Bachir Affar, Stéphane Richard, Jean‐Yves Masson
2020· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
31
citations
afffundno abstractunlabeled
Transcription-coupled nucleosome assembly
François Robert, Celia Jerónimo
2023· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
23
citations
fundno affno abstractunlabeled
Dissecting the biophysics and biology of intrinsically disordered proteins
Priya R. Banerjee, Alex S. Holehouse, Richard W. Kriwacki, Paul Robustelli, Hao Jiang, Alexander I. Sobolevsky +2 more
2023· article· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
21
citations
affno abstractunlabeled
H2A.Z and DNA methylation: irreconcilable differences
Michael S. Kobor, Matthew C. Lorincz
2009· article· en· Trends in Biochemical Sciences· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
18
citations
afffundunlabeled
Inheritance of Histone (H3/H4): A Binary Choice?
Nicole J. Francis, Djamouna Sihou
2020· review· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
11
citations
affno abstractunlabeled
Does Too Much MAGIC Lead to Mitophagy?
Mohamed A. Eldeeb, Richard P. Fahlman
2018· letter· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
9
citations
afffundno abstractunlabeled
ER-associated Protein Degradation at Atomic Resolution
Mohamed A. Eldeeb, Richard P. Fahlman, Marek Michalak
2020· letter· en· Trends in Biochemical Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Using graphs and charts in scientific figures
Karol Buda, Kateřina Čermáková, H. Courtney Hodges, Eugenio F. Fornasiero, Shahar Sukenik, Alex S. Holehouse
2023· article· en· Trends in Biochemical Sciences· Computer Science
machine prediction:candidate · metaresearchconsensus · none
2
citations

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