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Record W4382363527 · doi:10.1158/1078-0432.ccr-22-3146

Early Clearance of Plasma <i>Epidermal Growth Factor Receptor</i> Mutations as a Predictor of Outcome on Osimertinib in Advanced Non–Small Cell Lung Cancer; Exploratory Analysis from AURA3 and FLAURA

2023· article· en· W4382363527 on OpenAlexaff
Jhanelle E. Gray, Myung‐Ju Ahn, Geoffrey R. Oxnard, Frances A. Shepherd, Fumio Imamura, Ying Cheng, Isamu Okamoto, Byoung Chul Cho, Meng‐Chih Lin, Yi‐Long Wu, Margarita Majem, Oliver Gautschi, Michael Boyer, Krishna C. Bulusu, Aleksandra Markovets, J. Carl Barrett, Rachel Hodge, Astrid McKeown, Ryan J. Hartmaier, Juliann Chmielecki, Vassiliki A. Papadimitrakopoulou, Suresh S. Ramalingam

Bibliographic record

VenueClinical Cancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsOsimertinibLung cancerErlotinibMedicineT790MGefitinibInternal medicineOncologyEpidermal growth factor receptorTyrosine-kinase inhibitorConfidence intervalGenotypingCancerGenotypeBiology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

How this classification was reachedexpand

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)0.001
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 score0.005
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.116
GPT teacher head0.482
Teacher spread0.366 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations60
Published2023
Admission routes1
Has abstractyes

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