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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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Hydrology and Watershed Management Studies
Retraction
Abstract
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Study design
Label agreement
Label status

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
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

4,502 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.
4,502 works in the cohort · of 4,299,418page 71 of 91

Labels cover 5 of 4,502 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 4,502 of 4,502 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.

afffundunlabeled
Comment on hess-2022-306
Joel Harms, Julien Jean Malard-Adam, Jan Adamowski, Ashutosh Sharma, Albert Nkwasa
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Reply on RC2
Wouter Knoben
2021· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Comment on essd-2023-398
2024· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Reply on RC2
Mina Faghih
2021· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Responses to Reviewer #1
Paul H. Whitfield
2020· preprint· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affaboutunlabeled
Comment on hess-2022-96
Sara Sadri, J. S. Famiglietti, Ming Pan, Hylke E. Beck, Aaron Berg, Eric F. Wood
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundaboutunlabeled
Comment on gmd-2021-336
Robert Chlumsky, James R. Craig, Simon Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown +1 more
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Reply on RC1
Mina Faghih
2021· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Canadian River Watershed Data Report
Texas Stream Team
2010· article· en· The Meadows Center for Water and the Environment. <a href="https://www.meadowscenter.txstate.edu/Publications.html">https://www.meadowscenter.txstate.edu/Publications.html</a>· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Comment on hess-2023-69
Janneke Remmers
2023· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundaboutunlabeled
Reply on RC5
Paul H. Whitfield
2021· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundaboutunlabeled
Reply on RC1
Zhihua He
2023· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundunlabeled
Comment on hess-2023-69
Robert Chlumsky, Juliane Mai, James R. Craig, Bryan A. Tolson
2023· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(98)80030-6
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
afffundaboutunlabeled
Comment on hess-2022-264
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Comment on gmd-2021-212
Jiming Jin, Lei Wang, Jie Yang, Bingcheng Si, Guo‐Yue Niu
2021· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Comment on gmd-2022-16
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Reply on RC2
Louisa Oldham
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Instant Runoff Voting in Canada
2024· article· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Comment on gmd-2022-135
Luca Trotter, Wouter Knoben, Keirnan Fowler, Margarita Saft, Murray Peel
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundaboutunlabeled
Reply on RC1
Paul H. Whitfield
2021· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Comment on hess-2021-244
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, Lide Tian
2021· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Comment on hess-2023-187
Keith Beven
2023· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Creating synthetic meteorological data for ecosystem modeling
David T. Price
2008· article· en· 18th Conference on Atmospheric BioGeosciences/28th Conference on Agricultural and Forest Meteorology/28th Conference on Hurricanes and Tropical Meteorology<br> (28 April–2 May 2008)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Index
Ivan Martini, Victor R. Baker, Guillermina Garzón
2002· paratext· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundaboutunlabeled
Comment on hess-2022-113
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig +14 more
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations

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