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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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Pregnancy and preeclampsia studies
Retraction
Abstract
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Label agreement
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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.

3,744 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
3,744 works in the cohort · of 4,299,418page 74 of 75

Labels cover 13 of 3,744 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 3,744 of 3,744 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 affno abstractunlabeled
Rimouski-Neigette
2001· article· en· Érudit (Université de Montréal)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
0wj0ej0ejeoneononeononeoneon
2022· other· ar· Bulletin of Miscellaneous Information (Royal Gardens Kew)· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
Change Stories
2012· article· en· Sound Ideas (University of Puget Sound)· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affno abstractunlabeled
Étudier au Québec
2015· other· fr· Bibliothèque et Archives nationales du Québec (Québec government)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Evaluation of the Performance of fullPIERS (Preeclampsia Integrated Estimate of Risk Scoring) in Predicting Maternal-Fetal Complications in Congolese Women with Preeclampsia
Jean Pierre Elongi Moyene, Dophie Tshibuela Beya, Passy Kimena Nyota, Jérémie Muwonga Masidi, Elisabeth Lumbala Kilembo, Aliocha Nkodila Natuhoyila +2 more
2025· article· en· Journal of Obstetrics and Gynaecology Canada· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
[69-OR]
Darya Kurowecki, David Armstrong, Amanda Huynh, Marie Vasiliou, Shital Gandhi
2015· article· en· Pregnancy Hypertension· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
“GPI signal lost”: Implications for preeclampsia
Andrea Álvarez-Sánchez, Johanna Grinat, Paula Doria-Borrell, Marta Malenchini, Maravillas Mellado-López, Salvador Meseguer +2 more
2025· article· en· Placenta· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
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How this was built: Screen · Findings · About