MétaCan
Menu
Back to cohort
Record W4401419219 · doi:10.1016/j.healun.2024.05.010

International Society for Heart and Lung Transplantation Guidelines for the Evaluation and Care of Cardiac Transplant Candidates—2024

2024· article· en· W4401419219 on OpenAlexaff
Yael Peled, Anique Ducharme, M. Kittleson, Neha Bansal, Josef Stehlik, Shahnawaz Amdani, Diyar Saeed, Richard Cheng, Brian Clarke, Fabienne Dobbels, Maryjane Farr, JoAnn Lindenfeld, Lazaros A. Nikolaidis, Jignesh Patel, Deepak Acharya, Dimpna C. Albert, Saima Aslam, Alejandro Bertolotti, Michael Chan, Sharon Chih, Monica Colvin, María G. Crespo‐Leiro, David A. D’Alessandro, Kevin P. Daly, Carles Díez‐López, Anne I. Dipchand, Stephan Ensminger, Melanie D. Everitt, Alexander Fardman, Marta Farrero, David S. Feldman, Christiana Gjelaj, Matthew L. Goodwin, Kimberly Harrison, Eileen Hsich, Emer Joyce, Tomoko S. Kato, Daniel Kim, Me‐Linh Luong, Haifa Lyster, Marco Masetti, Lígia Neres Matos, Johan Nilsson, Pierre‐Emmanuel Noly, Vivek Rao, Katrine Rolid, Kelly Schlendorf, Martin Schweiger, Joseph A. Spinner, Madeleine Townsend, Maxime Tremblay‐Gravel, Simon Urschel, Jean‐Luc Vachiéry, A. Velleca, G. Waldman, James Walsh

Bibliographic record

VenueThe Journal of Heart and Lung Transplantation · 2024
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversité de MontréalUniversity of AlbertaStollery Children's HospitalHospital for Sick ChildrenSickKids FoundationUniversity of TorontoUniversity of Alberta HospitalAlberta Hospital EdmontonUniversity of OttawaSt. Paul's HospitalMontreal Heart Institute
Fundersnot available
KeywordsMedicineLung transplantationTransplantationGuidelineIntensive care medicineHeart transplantationInternal medicinePathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0040.004
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0060.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.408
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations185
Published2024
Admission routes1
Has abstractno

Explore more

Same venueThe Journal of Heart and Lung TransplantationSame topicTransplantation: Methods and OutcomesFrench-language works237,207