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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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Palliative Care and End-of-Life Issues
Retraction
Abstract
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Study design
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.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

5,852 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.
5,852 works in the cohort · of 4,299,418page 86 of 118

Labels cover 26 of 5,852 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 5,852 of 5,852 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
Dying due to terminal illness.
H. Powell
2011· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Role of the Editorial Board
Tracey A. Hotta
2018· article· en· Plastic Surgical Nursing· Medicine
machine prediction:candidate · metaresearchconsensus · none
0
citations
affunlabeled
Mourir chez soi
Brigitte Gagnon Kiyanda, Geneviève Dechêne, Robert Marchand
2015· article· fr· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The relationship between the strength of religious faith and spirituality and the level of acceptance of illness in a group of patients under home palliative care. Part 3. Spirituality and its conditioning, as well as the impact on the acceptance of illness
Grzegorz Nowicki, Renata Ziółek, Alina Deluga, Agnieszka Bartoszek, Zdzisława Szadowska-Szlachetka, Barbara Ślusarska
2020· article· en· Medycyna Paliatywna· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Introduction
Susan K MacRae
2008· book-chapter· en· Cambridge University Press eBooks· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Die Kunst den Tod ins Leben zu lassen
Nathalie Zeindler
2020· article· de· Schweizerische Ärztezeitung· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
OUR CONTRIBUTIVE LIFE
Phyllis Malpas
2012· editorial· en· Gastroenterology Nursing· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Nurses' experiences with assisted death
A. A. Fulton
2021· article· en· cIRcle (University of British Columbia)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
afffundaboutunlabeled
Derivation and validation of a mortality risk prediction model in older adults needing home care: Updating the RESPECT (Risk Evaluation for Support: Predictions for Elder-Life in their Communities Tool) algorithm for use with data from the interRAI Home Care Assessment System
Maya Murmann, Douglas G. Manuel, Peter Tanuseputro, Carol Bennett, Michael Pugliese, Wenshan Li +2 more
2024· preprint· en· F1000Research· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Quality end-of-life care.
G Skrinskas
2002· letter· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.70266/9783886177387
2000· book· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affaboutunlabeled
Tools to Predict Survival
Peggy Oldfield
2006· article· en· AJN American Journal of Nursing· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The Growth of Palliative Care.
Donald L Pendley
2017· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
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