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Record W4400338866 · doi:10.1016/j.xjtc.2024.06.018

Extra-pleural pneumonectomy: How I teach it

2024· editorial· en· W4400338866 on OpenAlexaff
Phil C Honest, Laura Donahoe, Marc de Perrot

Bibliographic record

VenueJTCVS Techniques · 2024
Typeeditorial
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExtrapleural PneumonectomyMedicineMesotheliomaPneumonectomySurgeryNivolumabGeneral surgeryInternal medicineOncologyLung cancerImmunotherapyPathologyCancer

Abstract

fetched live from OpenAlex

Extrapleural pneumonectomy (EPP) is a complex procedure used to treat malignant pleural mesothelioma (MPM). Despite advances in therapy, MPM continues to have a very poor prognosis. Currently, nonsurgical management with combinations of chemotherapy and immunotherapy provide overall survival of about 18 months.1,2 EPP is the most extensive surgical option for MPM, involving the en bloc resection of the lung, parietal and visceral pleura, diaphragm, and pericardium, and is commonly used as a component of multimodal therapy to provide an aggressive treatment option with the hope of long-term remission.

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)0.003
metaresearch head score (Gemma)0.011
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0020.001
Research integrity0.0080.019
Insufficient payload (model declined to judge)0.0090.007

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 head0.011
GPT teacher head0.298
Teacher spread0.286 · 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
GenreEditorial

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
Published2024
Admission routes1
Has abstractyes

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