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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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RNA and protein synthesis mechanisms
Retraction
Abstract
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Label agreement
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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.

affaffiliation
fundfunder
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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.

3,072 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
3,072 works in the cohort · of 4,299,418page 59 of 62

Labels cover 2 of 3,072 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 3,072 of 3,072 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
Counting, generating and sampling tree alignments
Cédric Chauve, Julien Courtiel, Yann Ponty
2015· preprint· en· arXiv (Cornell University)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Finding Attractors on a Folding Energy Landscape
Wilfred Ndifon, Jonathan Dushoff
2011· book-chapter· en· IGI Global eBooks· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Structural Analysis of Ribozymes
Jonathan Ouellet, Sirinart Ananvoranich, Jean‐Pierre Perreault
2000· other· en· Encyclopedia of Analytical Chemistry· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
On the emergence of structural complexity in RNA replicators
Carlos Oliver, Vladimir Reinharz, Jérôme Waldispühl
2017· preprint· en· bioRxiv (Cold Spring Harbor Laboratory)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Pseudoknot-Generating Operation
Da-Jung Cho, Yo-Sub Han, Timothy Ng, Kai Salomaa
2016· book-chapter· en· Lecture notes in computer science· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
ATP‐mediated amino acid recognition by GlnRS
Eleonora M. Corigliano, Charlotte Habegger‐Polomat, Jacques Lapointe, John J. Perona
2006· article· en· The FASEB Journal· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Chargaff’s Cluster Rule
Donald R. Forsdyke
2010· book-chapter· en· Evolutionary Bioinformatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations

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