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Record W4253318261 · doi:10.22374/cjgim.v10i2.28

Update on Lung Cancer

2015· article· en· W4253318261 on OpenAlexaffvenue
Jason Agulnik

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityJewish General HospitalCentre Hospitalier Universitaire de SherbrookeMcGill University Health CentreUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineLung cancerLung cancer stagingRadiosurgeryLungRadiologyOncologyInternal medicineRadiation therapy

Abstract

fetched live from OpenAlex

Summary Investigation and treatment of lung cancer has changed dramatically since the last articles in this journal in 2008. These changes include a new study on lung cancer staging, a new tumour, node, metastasis (TNM) classification, linear endoscopic ultrasound as a first-line test for mediastinal staging, investigation and follow-up of ground glass and mixed-lung nodules, radiosurgery for inoperable patients with localized lung tumours, and molecular tests and targeted therapies for advanced non-small cell lung cancer.

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)0.006
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: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0180.012

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 head0.033
GPT teacher head0.340
Teacher spread0.307 · 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
GenreReview

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
Published2015
Admission routes2
Has abstractyes

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Same venueCanadian Journal of General Internal MedicineSame topicLung Cancer Diagnosis and TreatmentFrench-language works237,207