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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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Marine and fisheries research
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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
venuejournal
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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.

5,649 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.
5,649 works in the cohort · of 4,299,418page 13 of 113

Labels cover 6 of 5,649 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 5,649 of 5,649 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
Shifts in fisheries management: adapting to regime shifts
Jacquelynne R. King, Gordon A. McFarlane, André E. Punt
2014· article· en· Philosophical Transactions of the Royal Society B Biological Sciences· Environmental Science
machine prediction:candidate · noneconsensus · none
79
citations
venueno affunlabeled
10.1016/s0967-0653(97)82984-5
A.E. Hill, Judith Brown, Liam Fernand
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
78
citations
affunlabeled
Estimating stock status from relative abundance and resilience
Rainer Froese, Henning Winker, Gianpaolo Coro, Nazlı Demirel, Athanassios C. Tsikliras, Donna Dimarchopoulou +4 more
2019· article· en· ICES Journal of Marine Science· Environmental Science
machine prediction:candidate · noneconsensus · none
78
citations
affunlabeled
Poleward bound: adapting to climate-driven species redistribution
Jess Melbourne-Thomas, Asta Audzijonytė, M Brasier, Katherine A. Cresswell, Hannah E. Fogarty, Marcus Haward +13 more
2021· review· en· Reviews in Fish Biology and Fisheries· Environmental Science
machine prediction:candidate · noneconsensus · none
77
citations
afffundunlabeled
Averting a global fisheries disaster
Boris Worm
2016· letter· en· Proceedings of the National Academy of Sciences· Environmental Science
machine prediction:candidate · noneconsensus · none
77
citations
venueno affunlabeled
Recruitment variation related to fecundity in marine fishes
S J Rickman, Nicholas K. Dulvy, Simon Jennings, John D. Reynolds
2000· article· en· Canadian Journal of Fisheries and Aquatic Sciences· Environmental Science
machine prediction:candidate · noneconsensus · none
76
citations
affunlabeled
Food for thought: pretty good multispecies yield
Anna Rindorf, Catherine M. Dichmont, Phillip S. Levin, Pamela M. Mace, Sean Pascoe, Raúl Prellezo +6 more
2016· article· en· ICES Journal of Marine Science· Environmental Science
machine prediction:candidate · noneconsensus · none
76
citations
affno abstractunlabeled
Collecting zooplankton
D. D. Sameoto, Peter H. Wiebe, Jeffrey A. Runge, L. Postel, Jennifer A. Dunn, C. B. Miller +1 more
2000· book-chapter· en· Elsevier eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
76
citations
fundno affunlabeled
Ecosystems say good management pays off
Elizabeth A. Fulton, André E. Punt, Catherine M. Dichmont, Chris J. Harvey, Rebecca Gorton
2018· article· en· Fish and Fisheries· Environmental Science
machine prediction:candidate · noneconsensus · none
76
citations
venueno affunlabeled
10.1016/0967-0653(96)87554-5
Colin Summerhayes, S. A. Thorpe
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
76
citations
affno abstractunlabeled
The management of high seas fisheries
Trond Bjørndal, Veijo Kaitala, Marko Lindroos, Gordon R. Munro
2000· article· en· Annals of Operations Research· Environmental Science
machine prediction:candidate · noneconsensus · none
74
citations

How this was built: Screen · Findings · About