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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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Advanced Fluorescence Microscopy 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.

986 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.
986 works in the cohort · of 4,299,418page 4 of 20

Labels cover 1 of 986 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 986 of 986 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
Putting the axonal periodic scaffold in order
Christophe Leterrier
2021· review· en· Current Opinion in Neurobiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
51
citations
fundno affunlabeled
Real-time high dynamic range laser scanning microscopy
Claudio Vinegoni, Christine Leon Swisher, Paolo Fumene Feruglio, Randy J. Giedt, D. Rousso, Shawn Stapleton +1 more
2016· article· en· Nature Communications· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
48
citations
affunlabeled
Deep Learning-Based Point-Scanning Super-Resolution Imaging
Linjing Fang, Fred Monroe, Sammy Weiser Novak, Lyndsey M. Kirk, Cara R. Schiavon, Seungyoon B. Yu +10 more
2019· preprint· en· bioRxiv (Cold Spring Harbor Laboratory)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
47
citations
affno abstractunlabeled
Optical microscopy in photosynthesis
Richard Cisek, Leigh Spencer, Nicole Prent, Donatas Zigmantas, George S. Espie, Virginijus Barzda
2009· review· en· Photosynthesis Research· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
41
citations
afffundno abstractunlabeled
An Engineered Monomeric Zoanthus sp. Yellow Fluorescent Protein
Hiofan Hoi, Elizabeth S. Howe, Yidan Ding, Wei Zhang, Michelle A. Baird, Brittney Sell +3 more
2013· article· en· Chemistry & Biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
40
citations
affunlabeled
Data reconstruction by generalized deconvolution
Mauricio D. Sacchi, D. J. Verschuur, Paul Zwartjes
2004· article· en· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
39
citations
affunlabeled
Multiphoton microscopy in defining liver function
Camilla A. Thorling, Dorothy H. Crawford, Frank J. Burczynski, Xin Liu, Ian Liau, Michael S. Roberts
2014· review· en· Journal of Biomedical Optics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
36
citations

How this was built: Screen · Findings · About