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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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International Journal of Law and Psychiatry
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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.

232 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.
232 works in the cohort · of 4,299,418page 3 of 5

Labels cover 0 of 232 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 232 of 232 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.

affno abstractunlabeled
Can sexual offenders be treated?
John Bradford, Paul Fedoroff, Sanjiv Gulati
2013· review· en· International Journal of Law and Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
18
citations
afffundno abstractunlabeled
Weapon focus in sexual assault memories of prostitutes
Barry S. Cooper, Margaret Kennedy, Hugues Hervé
2002· article· en· International Journal of Law and Psychiatry· Engineering
machine prediction:candidate · noneconsensus · none
17
citations
afffundno abstractunlabeled
Do intensive services obviate the need for CTOs?
Richard O’Reilly, Deborah Corring, Julie Richard, Cathy Plyley, Luljeta Pallaveshi
2016· article· en· International Journal of Law and Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Human rights vs. public protection
Laura Davidson
2002· article· en· International Journal of Law and Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
14
citations
affno abstractunlabeled
Measurement-based care in forensic psychiatry
Graham Glancy, Maxym Choptiany, Roland M. Jones, Sumeeta Chatterjee
2020· article· en· International Journal of Law and Psychiatry· Medicine
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
Forensic psychiatry in Pakistan
Tariq Hassan, Asad Tamizuddin Nizami, Sarah Hirji
2015· review· en· International Journal of Law and Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
12
citations
affno abstractunlabeled
Forensic psychiatry in Chile
Emily E. St.Denis, Enrique Sepúlveda, Carlos Téllez, Julio Arboleda‐Flórez, Heather Stuart, Miu Lam
2012· article· en· International Journal of Law and Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
12
citations
affaboutno abstractunlabeled
Forensic Psychiatric Services in British Columbia
Derek Eaves, Diane J. Lamb, George Tien
2000· review· en· International Journal of Law and Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
9
citations

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