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Record W3191683197 · doi:10.1016/j.healun.2021.07.016

ISHLT consensus document on lung transplantation in patients with connective tissue disease: Part II: Cardiac, surgical, perioperative, operative, and post-operative challenges and management statements

2021· article· en· W3191683197 on OpenAlexaff
C. Bermúdez, M. Crespo, Oksana A. Shlobin, Edward Cantu, Jeremy A. Mazurek, Deborah J. Levine, Jacob T. Gutsche, Manreet Kanwar, Göran Dellgren, Errol L. Bush, Gustavo A. Heresi, Marcelo Cypel, Rachel A. Hadler, Nicholas Kolatis, Verónica Franco, Luke Benvenuto, Joshua J. Mooney, Matthew R. Pipeling, Christopher S. King, H. Mannem, Sanjeev Raman, Christiane Knoop, Aaron Douglas, Olaf Mercier

Bibliographic record

VenueThe Journal of Heart and Lung Transplantation · 2021
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineLung transplantationPerioperativeCTDTransplantationIntensive care medicineConnective tissuePulmonary hypertensionRight ventricular failureLungConnective tissue diseaseDiseaseSurgeryInternal medicinePathologyAutoimmune disease

Abstract

fetched live from OpenAlex

Patients with connective tissue disease (CTD) present unique surgical, perioperative, operative, and postoperative challenges related to the often underlying severe pulmonary hypertension and right ventricular dysfunction. The International Society for Heart and Lung Transplantation-supported consensus document on lung transplantation in patients with CTD standardization addresses the surgical challenges and relevant cardiac involvement in the perioperative, operative, and postoperative management in patients with CTD.

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)0.034
metaresearch head score (Gemma)0.048
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: Other · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0050.004
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0070.005

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 head0.014
GPT teacher head0.332
Teacher spread0.317 · 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
GenreOther

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

Citations12
Published2021
Admission routes1
Has abstractyes

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