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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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Computers in Biology and Medicine
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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.

415 results · 1 filter active ·
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20012025
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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.
415 works in the cohort · of 4,299,418page 7 of 9

Labels cover 0 of 415 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 415 of 415 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
Feature-based MRI data fusion for cardiac arrhythmia studies
Karl Magtibay, Mohammadali Beheshti, F. H. Foomany, Stéphane Massé, Patrick F.H. Lai, Nima Zamiri +5 more
2016· article· en· Computers in Biology and Medicine· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
Whole slide image representation in bone marrow cytology
Youqing Mu, Hamid R. Tizhoosh, Taher Dehkharghanian, Clinton J.V. Campbell
2023· article· en· Computers in Biology and Medicine· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
BitterEN: A novel ensemble model for the identification of bitter peptide
Md. Fahim Sultan, Tasmin Karim, Md. Shazzad Hossain Shaon, Md. Mamun Ali, Sobhy M. Ibrahim, Mst Shapna Akter +3 more
2025· article· en· Computers in Biology and Medicine· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
Stress classification with in-ear heartbeat sounds
Danielle Benesch, Bérangère Villatte, Alain Vinet, Sylvie Hébert, Jérémie Voix, Rachel Bouserhal
2024· article· en· Computers in Biology and Medicine· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Domain-aware contrastive learning for ultrasound hip image analysis
Abhilash Rakkunedeth Hareendranathan, Arpan Tripathi, Mahesh Raveendranatha Panicker, Yuyue Zhou, Jessica Knight, Jacob L. Jaremko
2022· article· en· Computers in Biology and Medicine· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
ACU<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si3.svg" display="inline" id="d1e1379"><mml:msup><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math>E-Net: A novel predict–refine attention network for segmentation of soft-tissue structures in ultrasound images
Sharanya Balachandran, Xuebin Qin, Chen Jiang, Ehsan Seyed Blouri, Amir Forouzandeh, Masood Dehghan +4 more
2023· article· lv· Computers in Biology and Medicine· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
afffundno abstractunlabeled
Insights into the suitability of utilizing brown rats (Rattus norvegicus) as a model for healing spinal cord injury with epidermal growth factor and fibroblast growth factor-II by predicting protein-protein interactions
Nashira Grigg, Andrew Schoenrock, Kevin Dick, James R. Green, Ashkan Golshani, Alex Wong +3 more
2018· article· en· Computers in Biology and Medicine· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
afffundunlabeled
Turbulent-like blood flow in neo-aorta in post-norwood patients
Vivian Tan, Ankavipar Saprungruang, Brandon Peel, Christopher K. Macgowan, Christoph Haller, David J. Barron +3 more
2025· article· en· Computers in Biology and Medicine· Medicine
machine prediction:candidate · noneconsensus · none
3
citations

How this was built: Screen · Findings · About