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Record W2075483442 · doi:10.3747/co.19.1113

Drug Resistance and Its Significance for Treatment Decisions in Non-Small-Cell Lung Cancer

2012· article· en· W2075483442 on OpenAlexaffvenue
Elena Tsvetkova, G. Goss

Bibliographic record

VenueCurrent Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineLung cancerDrugDrug resistanceCancer drugsIntensive care medicineBioinformaticsPharmacologyOncologyBiologyGenetics

Abstract

fetched live from OpenAlex

Non-small-cell lung cancer (nsclc) constitutes about 85% of all lung cancers. Approximately 50% of patients diagnosed with nsclc present with advanced disease (stage iii or iv) that is not amenable to curative treatment. The number of patients with stage iiib or iv disease who are alive at 1 year after diagnosis has increased from 10% in the untreated population in the early 1980s to 50% in patients with a good performance status receiving treatment today. However, those statistics remain dismal, and the two dominant reasons are the large number of patients diagnosed with advanced-stage disease and the observed primary or secondary resistance to current therapies. The present article addresses the question of drug resistance in lung cancer, focusing on subjects that are currently topical and under intense scrutiny.

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 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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.083
GPT teacher head0.451
Teacher spread0.368 · 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 designNot applicable
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

Citations93
Published2012
Admission routes2
Has abstractyes

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