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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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Infrared Target Detection Methodologies
Retraction
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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
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

286 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.
286 works in the cohort · of 4,299,418page 4 of 6

Labels cover 1 of 286 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 286 of 286 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
AT20G: an all sky blind survey at 20GHz
R. D. Ekers, M. Massardi, E. M. Sadler
2008· article· en· Proceedings of From Planets to Dark Energy: the Modern Radio Universe — PoS(MRU)· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Tolerancing model for better prediction
Nathalie Blanchard, Frédéric Lamontagne, Mélanie Leclerc
2023· article· en· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
The Truth about Astroimaging
Wil Milan
2000· article· en· Journal of the Royal Astronomical Society of Canada· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Development of an Infrared Imager
Sa Charlebois, Luc G. Fréchette, Dominique Drouin, Peter Ya, O. Moutanabbir, P. Desjardins +2 more
2017· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)85052-1
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Software thermal imager simulator
Loïc Le Noc, Ovidiu Pancrati, Michel Doucet, Denis Dufour, Benoît Debaque, Simon Turbide +5 more
2014· article· kn· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Review of Measuring Imagery
Xiao Ma, Yu Zhang
2013· article· en· Advances in Psychological Science· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)99712-z
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
AIMSsim Version 2.3.4 - User Manual
Oliver Schoenborn, Patrick Lachance, Nima Bahramifarid
2008· article· en· Defense Technical Information Center (DTIC)· Engineering
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About