MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Medical Imaging Techniques and Applications
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

2,749 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
2,749 works in the cohort · of 4,299,418page 55 of 55

Labels cover 4 of 2,749 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 2,749 of 2,749 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.

venueno affno abstractunlabeled
10.1016/s1541-9800(08)70333-8
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
New IAGLR Membership Categories
2012· article· en· Journal of Great Lakes Research· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
PET Attenuation Correction without Transmission Scan
Antonio Soriano, A. Orero, F. Sánchez, J. Benlloch, Antonio J. González, Carlos Correcher
2010· article· en· Mechatronic systems and control· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
afffundno abstractunlabeled
Seeing More, Treating Smarter
Pedro L. Esquinas, Fereshteh Yousefirizi, Ian Alberts, Nicolas A. Karakatsanis, Arman Rahmim, Carlos Uribe
2025· review· en· PET Clinics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/j.endend.2011.08.045
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
SciTools/nc-time-axis: v1.4.1
2022· other· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affaboutunlabeled
A25 Spect CT in neuroendocrine tumours
Robert H. Reid, I. Rachinski, Walter Kocha
2006· article· en· Nuclear Medicine Communications· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Who Uses SNOMED CT®?
Linda Bird
2025· book-chapter· en· Health information technology standards· Medicine
machine prediction:candidate · bibliometricsconsensus · none
0
citations
affunlabeled
Influencing absolute structure determination
A. L. Thompson
2011· article· en· Acta Crystallographica Section A Foundations of Crystallography· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
London Imaging Meeting 2021: Imaging for Deep Learning
Michael S. Brown, Javier Vázquez-Corral, Susan Farnand, Graham D. Finlayson, Rafał Mantiuk
2021· article· en· London Imaging Meeting· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/j.endend.2013.06.017
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Plutella hyperboreella Strand 1902
2013· article· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1553-3212(12)70194-2
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0029-7437(07)70627-4
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Wayde Compton
Heather Smyth
2024· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Optimization of wavelet processing of dynamic PET data
Nathaniel M. Alpert, Anthonin Reihlac, Tat T Chio, Ivan Selesnick
2005· article· en· Journal of Cerebral Blood Flow & Metabolism· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Detecting Dopamine Release via PCA of Residuals
Connor Bevington, Jordan Hanania, Ju-Chieh Cheng, Vesna Sossi
2021· article· en· 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About