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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.

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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.

14,021 results · 1 filter active ·
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20182025
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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.
14,021 works in the cohort · of 4,299,418page 2 of 281

Labels cover 57 of 14,021 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 14,021 of 14,021 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
Defining and benchmarking open problems in single-cell analysis
Malte D. Luecken, Scott Gigante, Daniel B. Burkhardt, Robrecht Cannoodt, Daniel Strobl, Nikolay S. Markov +43 more
2024· preprint· en· Research Square· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
16
citations
aboutno affgemma · bibliometricsgpt · bibliometricsmodels agree
Graph Neural Networks: a bibliometrics overview
Abdalsamad Keramatfar, Mohadeseh Rafiee, Hossein Amirkhani
2022· preprint· en· Research Square· Computer Science
machine prediction:candidate · bibliometricsconsensus · none
16
citations
affno abstractunlabeled
Managing biological invasions: the cost of inaction
Danish A. Ahmed, Emma J. Hudgins, Ross N. Cuthbert, Melina Kourantidou, Christophe Diagne, Phillip Joschka Haubrock +5 more
2021· preprint· en· Research Square· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Air Pollution in Bangladesh and Its Consequences
Salamat Khandker, ASM Mohiuddin, Sk Akhtar Ahmad, Alice McGushin, Alan Abelsohn
2022· preprint· en· Research Square· Environmental Science
machine prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Global economic impact of scuba dive tourism
Anna Schuhbauer, Fabio Favoretto, Terrance Wang, Octavio Aburto‐Oropeza, Enric Sala, Katherine D. Millage +7 more
2023· preprint· en· Research Square· Social Sciences
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Semantic Segmentation With Labeling Uncertainty and Class Imbalance
Patrik Olã Bressan, José Marcato, José Augusto Correa Martins, Maximilian Jaderson de Melo, Diogo Nunes Gonçalves, Daniel Matte Freitas +6 more
2021· preprint· en· Research Square· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
County-level ammonia emissions monitored worldwide
Enrico Dammers, Mark W. Shephard, Debora Griffin, Evan Chow, Evan J. White, Jonathan E. Hickman +9 more
2022· preprint· en· Research Square· Environmental Science
machine prediction:candidate · noneconsensus · none
12
citations

How this was built: Screen · Findings · About