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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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Single-cell and spatial transcriptomics
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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.

2,127 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.
2,127 works in the cohort · of 4,299,418page 8 of 43

Labels cover 2 of 2,127 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 2,127 of 2,127 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
High throughput automated analysis of big flow cytometry data
Albina Rahim, Justin Meskas, Sibyl Drissler, Alice Yue, Anna Lorenc, Adam G. Laing +5 more
2017· article· en· Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
30
citations
afffundunlabeled
Standardizing workflows in imaging transcriptomics with the abagen toolbox
Ross D. Markello, Aurina Arnatkevičiūtė, Jean‐Baptiste Poline, Ben Fulcher, Alex Fornito, Bratislav Mišić
2021· preprint· en· bioRxiv (Cold Spring Harbor Laboratory)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
30
citations
affunlabeled
Evolutionary convergence of sensory circuits in the pallium of amniotes
Eneritz Rueda-Alaña, Rodrigo Senovilla-Ganzo, Marco Grillo, Enrique Vázquez, Sergio Marco Salas, Tatiana Gallego‐Flores +16 more
2025· article· en· Science· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
29
citations
affno abstractunlabeled
Defining and benchmarking open problems in single-cell analysis
Malte D. Luecken, Scott Gigante, Daniel B. Burkhardt, Robrecht Cannoodt, Daniel Strobl, Nikolay S. Markov +19 more
2025· letter· en· Nature Biotechnology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaresearchconsensus · none
29
citations
affno abstractunlabeled
Causal machine learning for single-cell genomics
Alejandro Tejada-Lapuerta, Paul A. Bertin, Stefan Bauer, Hananeh Aliee, Yoshua Bengio, Fabian J. Theis
2025· review· en· Nature Genetics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
28
citations
afffundunlabeled
Data Standards for Flow Cytometry
Josef Špidlen, Robert Gentleman, Perry Haaland, Morgan G. I. Langille, Nolwenn Le Meur, Michael F. Ochs +4 more
2006· review· en· OMICS A Journal of Integrative Biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaresearchconsensus · none
28
citations
fundno affunlabeled
Alignment of single-cell trajectory trees with CAPITAL
Reiichi Sugihara, Yuki Kato, Tomoya Mori, Yukio Kawahara
2022· article· en· Nature Communications· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
27
citations

How this was built: Screen · Findings · About