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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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Proceedings of the World Congress on Civil, Structural, and Environmental Engineering
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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.

578 results · 1 filter active ·
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20162025
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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.
578 works in the cohort · of 4,299,418page 5 of 12

Labels cover 0 of 578 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 578 of 578 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.

venueno affunlabeled
Clay Soil Stabilization Using Sugarcane Ash and Lime
Magdi El-Emam, Mousa Attom, Naveed Ahmad
2025· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Forecast Rainfall Density by Utilizing Machine Learning Models
Sung‐Chi Hsu, Alok Kumar Sharma
2023· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
The Toxic Effect of Drug Residues on the Germination of Cultivated Plants
Szilárd Székely, Eszter Rápó, Katalin Mihályfalvi, Szende Tonk
2023· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Numerical Analysis of the Influence of Spalling in Slender RC Columns
Carmen Hernández Ibáñez, David L. Peña, Vicente Albero, Andrés Lapuebla Ferri, Héctor Saura
2023· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Gold Nanoparticles from Grape Pomace Wastes: Cosmetic and Biomedical Applications
Vito Rizzi, Jennifer Gubitosa, Anna Laurenzana, Francesca Scavone, Elena Frediani, Gabriella Fibbi +2 more
2023· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
3D Model Generation of CFS Members from Surface Data
Burcu Güldür Erkal
2019· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Multielemental Analysis of Pleural Effusion to Determine the Relationship Between Air Pollution and Lung Cancer
Ana Larissa Barbosa Sánchez, Ciro Eliseo Márquez Herrera, Martha Patricia Sierra Vargas, Ma. de Lourdes Guadalupe Flores Luna, Reina Torralba, Leticia Hernández‐Cadena +2 more
2024· article· en· Proceedings of the World Congress on Civil, Structural, and Environmental Engineering· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About