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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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Sensory Analysis and Statistical 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.

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.

428 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.
428 works in the cohort · of 4,299,418page 6 of 9

Labels cover 0 of 428 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 428 of 428 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.

afffundno abstractunlabeled
Carrot Juice Yogurts
Lihua Fan, Margaret A. Cliff
2017· book-chapter· en· Elsevier eBooks· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
3
citations
afffundno abstractunlabeled
Sensory characterization of conifer-based extracts for culinary uses
Afia Boumail, François Girard, Katherine H. Tanaka, Michael Bom Frøst, Sylvie L. Turgeon, Véronique Perreault
2024· article· en· International Journal of Gastronomy and Food Science· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Principal axes analysis of symbolic histogram variables
Sun Makosso‐Kallyth
2015· article· en· Statistical Analysis and Data Mining The ASA Data Science Journal· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
A test for psychometric function shift
Alexander D. Logvinenko, Yuri N. Tyurin, Martin Sawey
2011· article· en· Behavior Research Methods· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Scaling responses
David L. Streiner, Geoffrey R. Norman, John Cairney
2014· book· en· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Sequential optimization of drying and extraction processes for enhanced antioxidant recovery from <i>Parquetina nigrescens</i> leaves: Assessing drying parameters and extraction model reliability
Oladayo Adeyi, Goziya W. Dzarma, Ijeoma L. Princewill‐Ogbonna, Emmanuel Olusola Oke, B. I. Okolo, Ogueri Obinna Okechukwu +3 more
2025· article· en· The Canadian Journal of Chemical Engineering· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Dummy Variables
G. A. Darlington
2014· other· en· Wiley StatsRef: Statistics Reference Online· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Signal Detection Theory: Multidimensional
Helena Kadlec
2001· book-chapter· en· Elsevier eBooks· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Testing a Covariate
Melania Pintilie
2006· other· en· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About