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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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Video Surveillance and Tracking Methods
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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.

962 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.
962 works in the cohort · of 4,299,418page 5 of 20

Labels cover 1 of 962 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 962 of 962 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.

affno abstractunlabeled
CNN tracking based on data augmentation
Yong Wang, Xian Wei, Xuan Tang, Hao Shen, Lu Ding
2020· article· en· Knowledge-Based Systems· Computer Science
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Multiple Object Detection and Tracking in the Thermal Spectrum
Wassim A. El Ahmar, Dhanvin Kolhatkar, Farzan Erlik Nowruzi, Hamzah AlGhamdi, Jonathan Hou, Robert Laganière
2022· article· en· 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)· Computer Science
machine prediction:candidate · noneconsensus · none
18
citations
afffundunlabeled
Deep Attention Models for Human Tracking Using RGBD
Maryamsadat Rasoulidanesh, Srishti Yadav, Sachini Herath, Yasaman Vaghei, Shahram Payandeh
2019· article· en· Sensors· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
venueno affunlabeled
A Crowd Counting Framework Combining with Crowd Location
Jin Zhang, Sheng Chen, Sen Tian, Wenan Gong, Guoshan Cai, Ying Wang
2021· article· en· Journal of Advanced Transportation· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
venueno affunlabeled
LPYOLO: Low Precision YOLO for Face Detection on FPGA
Bestami Gunay, Sefa Burak Okcu, Hasan Şakir Bılge
2022· article· en· Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Reproducible evaluation of Pan-Tilt-Zoom tracking
Gengjie Chen, Pierre-Luc St-Charles, Wassim Bouachir, Guillaume-Alexandre Bilodeau, Robert Bergevin
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations

How this was built: Screen · Findings · About