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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.

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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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Geophysical Methods and Applications
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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.

1,000 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.
1,000 works in the cohort · of 4,299,418page 6 of 20

Labels cover 1 of 1,000 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 1,000 of 1,000 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
Issues and opportunities in urban forensic geology
Alastair Ruffell, Duncan Pirrie, Matthew Power
2013· article· en· Geological Society London Special Publications· Engineering
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Next generation of GUIDAR technology
Kristyn Harman, Bill Hodgins
2005· article· en· IEEE Aerospace and Electronic Systems Magazine· Engineering
machine prediction:candidate · noneconsensus · none
12
citations
affaboutunlabeled
Physical modelling of oil sands tailings consolidation
Amarebh R. Sorta, David C. Sego, Ward Wilson
2015· article· en· International Journal of Physical Modelling in Geotechnics· Engineering
machine prediction:candidate · noneconsensus · none
12
citations
aboutno affunlabeled
Transport of explosives I: TNT in soil and its equilibrium vapor
Bibiana Báez, Sandra N. Correa, Samuel P. Hernández‐Rivera, Maritza de Jesus, Miguel E. Castro, Nairmen Mina +1 more
2004· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Engineering
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Imaging tree root systems using ground penetrating radar (GPR) data in Brazil
Amanda Almeida Rocha, Welitom Rodrigues Borges, Mônica Giannoccaro Von Huelsen, Frederico Ricardo Ferreira Rodrigues de Oliveira e Sousa, Susanne Maciel, Janaína de Almeida Rocha +1 more
2024· article· en· Frontiers in Earth Science· Engineering
machine prediction:candidate · noneconsensus · none
11
citations
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How this was built: Screen · Findings · About