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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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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
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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.

2,769 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.
2,769 works in the cohort · of 4,299,418page 54 of 56

Labels cover 6 of 2,769 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 2,769 of 2,769 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
Similarity of Semantic Relations
2006· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Deconstructing word embedding algorithms
Kian Kenyon-Dean, Edward Newell, Jackie Chi Kit Cheung
2020· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Sculpture
2021· article· en· UND Scholarly Commons (University of North Dakota)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundaboutunlabeled
OurDirection
Sadra Abrishamkar, Jimmy Xiangji Huang
2018· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
fundno affunlabeled
Uncertainty-Guided Likelihood Tree Search
Julia Grosse, Ruotian Wu, Ahmad Rashid, Philipp Hennig, Pascal Poupart, Agustinus Kristiadi
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
A model of event knowledge.
Jeffrey L. Elman, Ken McRae
2019· article· en· Psychological Review· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
ExploreASL/ExploreASL: ExploreASL v1.8.0
Michael Stritt, Henk Mutsaerts, Jan Petr, Beatriz Padrela, Mathijs Dijsselhof, MauricePasternak +4 more
2021· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
THUNLP at TAC KBP 2013 in Entity Linking
Yan Wang, Yankai Lin, Zhiyuan Liu, Maosong Sun
2013· article· en· Theory and applications of categories· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2023· dataset· en· Global Biodiversity Information Facility· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About