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
Cardiac tumors and thrombi
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.

579 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.
579 works in the cohort · of 4,299,418page 11 of 12

Labels cover 0 of 579 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 579 of 579 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
Carney Complex
Anjelica Hodgson, Sara Pakbaz, Özgür Mete
2020· book-chapter· en· Encyclopedia of pathology· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
An odd looking lesion.
Lawrence Leung, Shawn Amyot
2011· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Danger of an R-2 (Debulking) Cardiac Tumor Resection
Nitish K. Dhingra, Abdullah H Ghunaim, Abdulaziz M Alhothali, Dambuza Nyamande, Robert J. Cusimano
2025· article· en· JACC Case Reports· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Chapter 33 Unfolding the map
2015· other· en· Directory of Open access Books (OAPEN Foundation)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Massive Thrombosis of the Left Ventricle: An Echo Round
Paolo Giuseppe Pino, Amedeo Pergolini, Giordano Zampi, Gaetano Pero, Giovanni Minardi
2013· article· en· Canadian Journal of Cardiology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Atypical left ventricular strain pattern in repaired TOF
Naser Alqahtani, Shanthi Chidambarathanu, Edythe Tham, Kumaradevan Punithakumar, Michelle Noga, Joseph J. Pagano
2025· article· en· Journal of Cardiovascular Magnetic Resonance· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Pericardial Sarcoma: “Invisible” on Radiology
Wei Cheng, Boxuan Hu, Xiaofan Peng, Xian Li, Yanshu Zhao, Daoquan Peng +2 more
2019· article· en· Canadian Journal of Cardiology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
PULMONARY VEIN INVASION, A RARE CAUSE OF AFIB
Jared Krainin, Cilia Nazef, David Goldgrab, Jacob Sanchez, Chad Harris, Jason Findlay +1 more
2025· article· en· Journal of the American College of Cardiology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Left Ventricular Papillary Fibroelastoma
Cristina M. Balboa, Souhayla Souaf, Jose M. Saro Suarez, Mohammad El‐Diasty, Ángel L. Fernández
2023· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About