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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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Advanced Proteomics Techniques and Applications
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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.

1,745 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.
1,745 works in the cohort · of 4,299,418page 1 of 35

Labels cover 4 of 1,745 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 1,745 of 1,745 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.

affno abstractunlabeled
A draft map of the human proteome
Min‐Sik Kim, Sneha M. Pinto, Derese Getnet, Raja Sekhar Nirujogi, Srikanth S. Manda, Raghothama Chaerkady +65 more
2014· article· en· Nature· Chemistry
machine prediction:candidate · noneconsensus · none
2,298
citations
affno abstractunlabeled
From genomics to proteomics
Mike Tyers, Matthias Mann
2003· article· en· Nature· Chemistry
machine prediction:candidate · noneconsensus · none
1,001
citations
affno abstractunlabeled
Analysis of protein complexes using mass spectrometry
Anne‐Claude Gingras, Matthias Gstaiger, Brian Raught, Ruedi Aebersold
2007· review· en· Nature Reviews Molecular Cell Biology· Chemistry
machine prediction:candidate · noneconsensus · none
698
citations
fundno affno abstractunlabeled
TCPA: a resource for cancer functional proteomics data
Jun Li, Yiling Lu, Rehan Akbani, Zhenlin Ju, Paul Roebuck, Wenbin Liu +8 more
2013· letter· en· Nature Methods· Chemistry
machine prediction:candidate · noneconsensus · none
538
citations
affunlabeled
A Mass Spectrometric-Derived Cell Surface Protein Atlas
Damaris Bausch‐Fluck, Andreas Hofmann, Thomas Bock, Andreas P. Frei, Ferdinando Cerciello, Hansjoerg Moest +13 more
2015· article· en· PLoS ONE· Chemistry
machine prediction:candidate · noneconsensus · none
476
citations
afffundunlabeled
De novo peptide sequencing by deep learning
Ngoc Hieu Tran, Xianglilan Zhang, Lei Xin, Baozhen Shan, Ming Li
2017· article· en· Proceedings of the National Academy of Sciences· Chemistry
machine prediction:candidate · noneconsensus · none
470
citations
affunlabeled
Discovery of Urinary Biomarkers
Trairak Pisitkun, Rose M. Johnstone, Mark A. Knepper
2006· review· en· Molecular & Cellular Proteomics· Chemistry
machine prediction:candidate · noneconsensus · none
403
citations
affno abstractunlabeled
Proteomics of organelles and large cellular structures
John R. Yates, Annalyn Gilchrist, Kathryn E. Howell, John Bergeron
2005· review· en· Nature Reviews Molecular Cell Biology· Chemistry
machine prediction:candidate · noneconsensus · none
390
citations
affunlabeled
<sup>18</sup> O Labeling: a tool for proteomics
Ian I. Stewart, Ty M. Thomson, Daniel Figeys
2001· article· en· Rapid Communications in Mass Spectrometry· Chemistry
machine prediction:candidate · noneconsensus · none
328
citations
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