MétaCan
Menu
← Back to cohort
Record W3215596070 · doi:10.1503/cmaj.211143-f

La transplantation pulmonaire dans le contexte de la COVID-19 aiguë : l’expérience du Programme de transplantation pulmonaire de Toronto

2021· letter· fr· W3215596070 on OpenAlexaffvenueabout
Jonathan Yeung, Marcelo Cypel, Cecilia Chaparro, Shaf Keshavjee

Bibliographic record

VenueCanadian Medical Association Journal · 2021
Typeletter
Languagefr
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Medicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)TransplantationLung transplantationGynecologyVirologyInfectious disease (medical specialty)Internal medicineDisease

Abstract

fetched live from OpenAlex

[Voir la version anglaise de l’article ici : www.cmaj.ca/lookup/doi/10.1503/cmaj.211143][1] Points clésUn homme de 60 ans, par ailleurs en bonne santé, a été hospitalisé pour une pneumonie associée à la COVID-19 qui a été traitée initialement par une ventilation non effractive, l’

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.588
Threshold uncertainty score0.819

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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 designCase report
Domainnot available
GenreCommentary

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

Citations0
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Medical Association Journal→Same topicLong-Term Effects of COVID-19→French-language works237,207→