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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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Computational Drug Discovery Methods
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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.

2,238 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.
2,238 works in the cohort · of 4,299,418page 1 of 45

Labels cover 4 of 2,238 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 2,238 of 2,238 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.

fundno affno abstractunlabeled
A Landscape of Driver Mutations in Melanoma
Eran Hodis, Ian R. Watson, Gregory V. Kryukov, Stefan T. Arold, Marcin Imieliński, Jean‐Philippe Theurillat +34 more
2012· article· en· Cell· Computer Science
machine prediction:candidate · noneconsensus · none
2,621
citations
afffundno abstractunlabeled
A Deep Learning Approach to Antibiotic Discovery
Jonathan Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andrés Cubillos-Ruiz, Nina M. Donghia +14 more
2020· article· en· Cell· Computer Science
machine prediction:candidate · noneconsensus · none
2,198
citations
affunlabeled
QSAR Modeling: Where Have You Been? Where Are You Going To?
Artem Cherkasov, Eugene Muratov, Denis Fourches, Alexandre Varnek, Igor I. Baskin, M Cronin +13 more
2013· article· en· Journal of Medicinal Chemistry· Computer Science
machine prediction:candidate · noneconsensus · none
2,073
citations
afffundunlabeled
DrugBank 4.0: shedding new light on drug metabolism
Vivian Law, Craig Knox, Yannick Djoumbou-Feunang, Tim Jewison, An Chi Guo, Yifeng Liu +11 more
2013· article· en· Nucleic Acids Research· Computer Science
machine prediction:candidate · noneconsensus · none
2,064
citations
afffundunlabeled
DrugBank 6.0: the DrugBank Knowledgebase for 2024
Craig Knox, Christen M. Klinger, Mark Franklin, Eponine Oler, Alexander E. Wilson, Allison Pon +35 more
2023· article· en· Nucleic Acids Research· Computer Science
machine prediction:candidate · noneconsensus · none
1,530
citations
affno abstractunlabeled
Software for molecular docking: a review
Nataraj Sekhar Pagadala, Khajamohiddin Syed, Jack A. Tuszyński
2017· review· en· Biophysical Reviews· Computer Science
machine prediction:candidate · noneconsensus · none
1,464
citations
affunlabeled
The IntAct molecular interaction database in 2012
Samuel Kerrien, Bruno Aranda, Lionel Breuza, Alan Bridge, F. Broackes-Carter, Carol Chen +16 more
2011· article· en· Nucleic Acids Research· Computer Science
machine prediction:candidate · scholarly_communicationconsensus · none
1,169
citations
affno abstractunlabeled
Automated design of ligands to polypharmacological profiles
Jérémy Besnard, G.F. Ruda, Vincent Setola, Keren Abecassis, Ramona M. Rodriguiz, Xi‐Ping Huang +15 more
2012· article· en· Nature· Computer Science
machine prediction:candidate · noneconsensus · none
845
citations
affunlabeled
Applications of Deep Learning in Biomedicine
Polina Mamoshina, Armando Vieira, Evgeny Putin, Alex Zhavoronkov
2016· review· en· Molecular Pharmaceutics· Computer Science
machine prediction:candidate · noneconsensus · none
715
citations
fundno affunlabeled
Bacterial Metabolism and Antibiotic Efficacy
Jonathan Stokes, Allison J. Lopatkin, Michael A. Lobritz, James J. Collins
2019· review· en· Cell Metabolism· Computer Science
machine prediction:candidate · noneconsensus · none
616
citations
affunlabeled
Drug development in Alzheimer’s disease: the path to 2025
Jeffrey L. Cummings, Paul Aisen, Bruno Dubois, Lutz Frölich, Clifford R. Jack, Roy Jones +4 more
2016· review· en· Alzheimer s Research & Therapy· Computer Science
machine prediction:candidate · noneconsensus · none
455
citations
affno abstractunlabeled
Artificial intelligence for natural product drug discovery
Michael W. Mullowney, Katherine Duncan, Somayah S. Elsayed, Neha Garg, Justin J. J. van der Hooft, Nathaniel I. Martin +52 more
2023· review· en· Nature Reviews Drug Discovery· Computer Science
machine prediction:candidate · noneconsensus · none
390
citations
afffundno abstractunlabeled
Drug repurposing for antimicrobial discovery
Maya A. Farha, Eric D. Brown
2019· review· en· Nature Microbiology· Computer Science
machine prediction:candidate · noneconsensus · none
368
citations
afffundunlabeled
Systematic exploration of synergistic drug pairs
Murat Cokol, Hon Nian Chua, Murat Taşan, Beste Mutlu, Zohar Weinstein, Yo Suzuki +9 more
2011· article· en· Molecular Systems Biology· Computer Science
machine prediction:candidate · noneconsensus · none
327
citations

How this was built: Screen · Findings · About