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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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Cell Image Analysis Techniques
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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.

3,696 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.
3,696 works in the cohort · of 4,299,418page 2 of 74

Labels cover 7 of 3,696 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 3,696 of 3,696 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.

affunlabeled
Learning to Relate Images
Roland Memisevic
2013· review· en· IEEE Transactions on Pattern Analysis and Machine Intelligence· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
93
citations
fundno affno abstractunlabeled
Control of cell state transitions
Oleksii S. Rukhlenko, Melinda Halász, Nora Rauch, Vadim Zhernovkov, Thomas L. Prince, Kieran Wynne +6 more
2022· article· en· Nature· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
89
citations
affno abstractunlabeled
Towards multimodal foundation models in molecular cell biology
Haotian Cui, Alejandro Tejada-Lapuerta, Maria Brbić, Julio Sáez-Rodríguez, Simona Cristea, Hani Goodarzi +3 more
2025· article· en· Nature· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
88
citations
affno abstractunlabeled
Tackling reproducibility in academic preclinical drug discovery
Stephen V. Frye, Michelle R. Arkin, C.H. Arrowsmith, P. Jeffrey Conn, Marcie A. Glicksman, Emily A. Hull-Ryde +1 more
2015· review· en· Nature Reviews Drug Discovery· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaresearchconsensus · none
85
citations
afffundno abstractunlabeled
Deformable organisms for automatic medical image analysis
Tim McInerney, Ghassan Hamarneh, Martha E. Shenton, Demetri Terzopoulos
2002· article· en· Medical Image Analysis· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
76
citations
affunlabeled
4D atlas of the mouse embryo for precise morphological staging
Michael D. Wong, Matthijs C. van Eede, Shoshana Spring, Stefan D. Jevtic, Julia C. Boughner, Jason P. Lerch +1 more
2015· article· en· Development· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
72
citations
affunlabeled
Contextual AI models for single-cell protein biology
Michelle M. Li, Yepeng Huang, Marissa Sumathipala, Man Liang, Alberto Valdeolivas, Ashwin N. Ananthakrishnan +3 more
2024· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
61
citations
afffundno abstractunlabeled
Multi-Image Colocalization and Its Statistical Significance
Patrick A. Fletcher, David R.L. Scriven, Meredith N. Schulson, Edwin D.W. Moore
2010· article· en· Biophysical Journal· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
58
citations
afffundunlabeled
Reagents for Mass Cytometry
Loryn P. Arnett, Rahul Rana, Wilson Wai-Yip Chung, Xiaochong Li, Mahtab Abtahi, Daniel Majonis +3 more
2023· review· en· Chemical Reviews· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
58
citations
affno abstractunlabeled
Automated Screening of Neurite Outgrowth
Peter Ramm, Yuriy Alexandrov, Andrzej Cholewinski, Yuriy Cybuch, Robert Nadon, Bohdan J. Soltys
2003· article· en· SLAS DISCOVERY· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
55
citations
affunlabeled
Computer vision for high content screening
Oren Kraus, Brendan J. Frey
2016· review· en· Critical Reviews in Biochemistry and Molecular Biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
53
citations
affunlabeled
Deep learning takes on tumours
Esther Landhuis
2020· article· en· Nature· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
51
citations
affunlabeled
Three-Dimensional (3D) Tumor Spheroid Invasion Assay
María Serena Vinci, Carol Box, Suzanne A. Eccles
2015· article· en· Journal of Visualized Experiments· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
50
citations

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