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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.

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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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Image and Object Detection 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.

affaffiliation
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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.

238 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.
238 works in the cohort · of 4,299,418page 3 of 5

Labels cover 1 of 238 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 238 of 238 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
AUTOMATIC DETECTION AND LABELLING OF PHOTOGRAMMETRIC CONTROL POINTS IN A CALIBRATION TEST FIELD
David Jarron, Mozhdeh Shahbazi, Derek D. Lichti, Radovan Radovanović
2019· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
afffundvenueunlabeled
Scale-space ridge detection with GPU acceleration
Michael Kinsner, David W. Capson, Allan D. Spence
2008· article· en· Conference proceedings - Canadian Conference on Electrical and Computer Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
fundno affunlabeled
Local Proofs Approaching the Witness Length
Noga Ron‐Zewi, Ron D. Rothblum
2024· preprint· en· Journal of the ACM· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Interpolation Methods for Global Vision Systems
Jacky Baltes, John Anderson
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
A Fast Algorithm for Template Matching
A. Kohandani, Otman Basir, Mohamed S. Kamel
2006· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
GROUND-PURITY INSPECTION FOR A GROUP OF ROBOTIC CLEANERS
Min‐Chie Chiu, Long-Jyi Yeh, Tian-Syung Lan, Wei-Cheng Liao, Chiu-Hung Chung
2012· article· en· Transactions of the Canadian Society for Mechanical Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Threaded C and Freezer OS
Jacky Baltes, Chris Iverach-Brereton, Chi Tai Cheng, John Anderson
2011· book-chapter· en· Communications in computer and information science· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
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