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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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Nutrition Reviews
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Retraction
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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.

307 results · 1 filter active ·
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20022025
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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.
307 works in the cohort · of 4,299,418page 1 of 7

Labels cover 1 of 307 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 307 of 307 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.

fundno affunlabeled
Biological fate of low-calorie sweeteners
Bernadene A. Magnuson, Michael C. Carakostas, Nadia H. Moore, Sylvia P. Poulos, A.G. Renwick
2016· review· en· Nutrition Reviews· Nursing
machine prediction:candidate · noneconsensus · none
318
citations
affunlabeled
Evidence of health benefits of canola oil
Lin Lin, Hanja Allemekinders, Angela Dansby, Lisa Campbell, Shaunda Durance-Tod, Alvin Berger +1 more
2013· review· en· Nutrition Reviews· Nursing
machine prediction:candidate · noneconsensus · none
282
citations
affunlabeled
Tea and Health
Siro Trevisanato, Young In Kim
2009· review· en· Nutrition Reviews· Medicine
machine prediction:candidate · noneconsensus · none
275
citations
affunlabeled
Dietary recommendations during the COVID-19 pandemic
Christianne de Faria Coelho‐Ravagnani, Flávia Campos Corgosinho, Fabiane La Flor Ziegler Sanches, Carla M. Prado, Alessandro Laviano, João Felipe Mota
2020· review· en· Nutrition Reviews· Medicine
machine prediction:candidate · noneconsensus · none
264
citations
affunlabeled
Microbiota and the gut–brain axis
John Bienenstock, Wolfgang Kunze, Paul Forsythe
2015· review· en· Nutrition Reviews· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
230
citations
affunlabeled
Human gut microbiota and its relationship to health and disease
Taylor C. Wallace, Francisco Guarner, Karen Madsen, Michael D. Cabana, Glenn R. Gibson, Eric Hentges +1 more
2011· review· en· Nutrition Reviews· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
230
citations
afffundaboutunlabeled
Curcumin and cancer: barriers to obtaining a health claim
Jessay G. Devassy, Ifeanyi D. Nwachukwu, Peter J.H. Jones
2015· review· en· Nutrition Reviews· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
229
citations
affunlabeled
Evidence-based criteria in the nutritional context
Jeffrey B. Blumberg, Robert P. Heaney, Michael Huncharek, Theresa O. Scholl, Meir J. Stampfer, Reinhold Vieth +2 more
2010· review· en· Nutrition Reviews· Medicine
machine prediction:candidate · noneconsensus · none
179
citations
affunlabeled
Probiotics and Their Potential Health Claims
Sylvia Santosa, Edward R. Farnworth, Peter J.H. Jones
2006· review· en· Nutrition Reviews· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
178
citations
affunlabeled
What Did Our Ancestors Eat?
Stanley M. Garn, William R. Leonard
2009· review· en· Nutrition Reviews· Arts and Humanities
machine prediction:candidate · noneconsensus · none
102
citations

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