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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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Arctic and Antarctic ice dynamics
Retraction
Abstract
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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.

5,542 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.
5,542 works in the cohort · of 4,299,418page 48 of 111

Labels cover 1 of 5,542 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 5,542 of 5,542 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.

aboutno affunlabeled
Ice edge failure process and modelling ice pressure
Kaj Riska
2018· review· en· Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences· Earth and Planetary Sciences
machine prediction:candidate · noneconsensus · none
8
citations
afffundno abstractunlabeled
Experimental study on a model azimuthing podded propulsor in ice
Jungyong Wang, Ayhan Akintürk, Neil Bose, Stephen J. Jones, Yun Young Song, Ho Hwan Chun +1 more
2008· article· en· Journal of Marine Science and Technology· Earth and Planetary Sciences
machine prediction:candidate · noneconsensus · none
8
citations
aboutno affunlabeled
Lagrangian transport across the upper Arctic waters in the Canada Basin
Francisco Balibrea‐Iniesta, Jiping Xie, Víctor J. García‐Garrido, Laurent Bertino, Ana M. Mancho, Stephen Wiggins
2018· article· en· Quarterly Journal of the Royal Meteorological Society· Earth and Planetary Sciences
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Fatigue damage from dynamic ice action - The FATICE project
Knut V. Høyland, Torodd Skjerve Nord, Joshua Turner, Vegard Hornnes, Ersegun Deniz Gedikli, Morten Bjerkås +3 more
2021· article· en· Research Repository (Delft University of Technology)· Earth and Planetary Sciences
machine prediction:candidate · noneconsensus · none
8
citations
fundvenueaboutno affunlabeled
Iceberg Shape Characterization
Richard McKenna
2005· article· en· NPARC· Earth and Planetary Sciences
machine prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
Ships in ice - a review
2004· article· en· NPARC· Earth and Planetary Sciences
machine prediction:candidate · noneconsensus · none
8
citations

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