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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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Biometric Identification and Security
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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.

394 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.
394 works in the cohort · of 4,299,418page 5 of 8

Labels cover 0 of 394 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 394 of 394 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
Template Security
Andy Adler, Raffaele Cappelli
2009· book-chapter· en· Encyclopedia of Biometrics· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Enhancing Biometric Security with Combinatorial and Permutational Multi-Fingerprint Authentication Strategies
Pratibha Singh, Hamman Samuel, Fehmi Jaafar, Darine Ameyed
2022· article· en· 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Multibiometrics and Data Fusion Standardization
Farzin Deravi, Richard T. Lazarick, Michael Thieme, Bian Yang, Jung Soh, Alessandro Triglia +1 more
2014· book-chapter· en· Encyclopedia of Biometrics· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
A Review on Facial Anti-spoofing Techniques
Veerpal Kaur, Prashant Kumar, Ashima Kukkar, Gagandeep Kaur, Amandeep Kaur
2024· review· en· Lecture notes in networks and systems· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Mobile Travel Credentials
David Bissessar, Maryam Hezaveh, Fayzah Alshammari, Carlisle Adams
2019· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Introduction
Issa Traoré, Mohammad S. Obaidat, Isaac Woungang
2018· book-chapter· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
2
citations
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