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Record W4286886313 · doi:10.1016/j.xjtc.2022.04.023

Commentary: Thoracoscopic right middle lobectomy—small but tricky

2022· editorial· en· W4286886313 on OpenAlexaff
Sadiq Al Khaboori, Sébastien Gilbert

Bibliographic record

VenueJTCVS Techniques · 2022
Typeeditorial
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineLung cancerMalignancyLungPneumonectomySurgeryGeneral surgeryOncologyInternal medicine

Abstract

fetched live from OpenAlex

As far as we are aware, there are many possible sequences of steps to complete a video-assisted thoracoscopic surgery lung resection without any clear demonstration of superiority from one to another. It is nevertheless important for trainees and mentors alike to develop a structured approach upon which to rely, especially when it comes to the right middle lobe, which harbors malignancy in only 5% to 7% of patients.1-4 Primary lung cancer of the right middle lobe is associated with a poorer prognosis, presumably because most of its lymphatic network drains directly into mediastinal lymph nodes.

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)0.002
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.050
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.005
Open science0.0040.001
Research integrity0.0500.045
Insufficient payload (model declined to judge)0.0100.009

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 head0.016
GPT teacher head0.306
Teacher spread0.290 · 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
Published2022
Admission routes1
Has abstractyes

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