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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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The Science of The Total Environment
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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.

4,078 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.
4,078 works in the cohort · of 4,299,418page 23 of 82

Labels cover 5 of 4,078 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 4,078 of 4,078 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.

fundno affno abstractunlabeled
Plant-insect vector-virus interactions under environmental change
Waqar Islam, Ali Noman, Hassan Naveed, Saad Alamri, Mohamed Hashem, Zhiqun Huang +1 more
2019· review· en· The Science of The Total Environment· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
54
citations
affno abstractunlabeled
Mercury mobilization in urban stormwater runoff
Chris S. Eckley, Brian A. Branfireun
2008· article· en· The Science of The Total Environment· Environmental Science
machine prediction:candidate · noneconsensus · none
54
citations
affno abstractunlabeled
Biodiversity responses to restoration across the Brazilian Atlantic Forest
João Paulo Romanelli, Paula Meli, João Paulo Bispo Santos, Igor Nogueira Jacob, Lukas Rodrigues Souza, André Vieira Rodrigues +7 more
2022· review· en· The Science of The Total Environment· Environmental Science
machine prediction:candidate · noneconsensus · none
53
citations
affno abstractunlabeled
Characterising dryland salinity in three dimensions
Qingsong Jiang, Jie Peng, Asim Biswas, Jie Hu, Ruiying Zhao, Kang He +1 more
2019· article· en· The Science of The Total Environment· Environmental Science
machine prediction:candidate · noneconsensus · none
53
citations
affno abstractunlabeled
Bioaugmentation of treatment wetlands – A review
Katharina Tondera, Florent Chazarenc, Pierre‐Luc Chagnon, Jacques Brisson
2021· review· en· The Science of The Total Environment· Environmental Science
machine prediction:candidate · noneconsensus · none
52
citations

How this was built: Screen · Findings · About