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Record W2802321489 · doi:10.21037/jtd.2018.03.121

A lower level of forced expiratory volume in one second predicts the poor prognosis of small cell lung cancer

2018· article· en· W2802321489 on OpenAlex
Hye Seon Kang, Ah Young Shin, Chang Dong Yeo, Ju Sang Kim, Yong Hyun Kim, Jin‐Woo Kim, Sang Haak Lee

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Thoracic Disease · 2018
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineCOPDInternal medicineLung cancerHazard ratioProportional hazards modelPulmonary function testingMultivariate analysisVital capacityRetrospective cohort studyLog-rank testOncologyLungConfidence intervalLung functionDiffusing capacity

Abstract

fetched live from OpenAlex

BACKGROUND: The impact of impaired pulmonary function on the clinical outcome of small cell lung cancer (SCLC) has not been examined. The objectives of this study were to compare the clinical characteristics and prognosis of SCLC patients with and without impaired pulmonary function and investigate predictors related to the pulmonary function of mortality in SCLC patients. METHODS: This is a retrospective multicenter study performed between January 2011 and December 2015. In all, 170 SCLC patients that were treated with chemotherapy and/or radiotherapy and had a pulmonary function test (PFT) were enrolled. Patients were divided into the chronic obstructive pulmonary disease (COPD) group and the non-COPD group. The overall survival (OS) was compared and predictors of worse OS were analyzed. RESULTS: less than 80% (HR =5.631; P=0.018) was independently associated with poor OS in patients with ED. CONCLUSIONS: , not COPD, was a predicting factor for poor treatment outcomes in SCLC patients.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.079
GPT teacher head0.383
Teacher spread0.304 · 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