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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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Nanoparticles: synthesis 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.

affaffiliation
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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.

1,200 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.
1,200 works in the cohort · of 4,299,418page 11 of 24

Labels cover 1 of 1,200 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 1,200 of 1,200 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
Toxic effects of colloidal nanosilver in zebrafish embryos
Maider Olasagasti, Antonietta Gatti, Federico Capitani, Alejandro Barranco, Miguel Ángel Pardo, Kepa Escuredo +1 more
2014· article· en· Journal of Applied Toxicology· Materials Science
machine prediction:candidate · noneconsensus · none
29
citations
fundno affno abstractunlabeled
Toxicogenomics: A New Paradigm for Nanotoxicity Evaluation
Sourabh Dwivedi, Quaiser Saquib, Bilal Ahmad, Sabiha M. Ansari, Ameer Azam, Javed Musarrat
2018· review· en· Advances in experimental medicine and biology· Materials Science
machine prediction:candidate · noneconsensus · none
28
citations
afffundno abstractunlabeled
Anti-microbiological and Anti-infective Activities of Silver
May Griffith, Klas I. Udekwu, Spyridon Gkotzis, Thien‐Fah Mah, Emilio I. Alarcón
2015· book-chapter· en· Engineering materials· Materials Science
machine prediction:candidate · noneconsensus · none
28
citations
afffundno abstractunlabeled
Instrumental approach toward understanding nano-pollutants
Mitra Naghdi, Sabrine Metahni, Yassine Ouarda, Satinder Kaur Brar, Ratul Kumar Das, Maximiliano Cledón
2017· article· en· Nanotechnology for Environmental Engineering· Materials Science
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Chemical Aspects of Nanoparticle Ecotoxicology
Laura Sigg, Yang Yue, Hannah Schug, Lena A. Kosak née Röhder, Flavio Piccapietra, Nikša Odžak +4 more
2014· article· en· CHIMIA International Journal for Chemistry· Materials Science
machine prediction:candidate · noneconsensus · none
24
citations

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