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Record W1701841458 · doi:10.1111/resp.12377

Molecular alterations in non‐small‐cell lung cancer: Perspective for targeted therapy and specimen management for the bronchoscopist

2014· review· en· W1701841458 on OpenAlexaff
Kasia Czarnecka‐Kujawa, Kazuhiro Yasufuku

Bibliographic record

VenueRespirology · 2014
Typereview
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineLung cancerAnaplastic lymphoma kinaseEpidermal growth factor receptorROS1CancerTargeted therapyPathologyOncologyLungMolecular pathologyInternal medicineAdenocarcinomaGene

Abstract

fetched live from OpenAlex

Major advances have occurred over the past decade in our understanding of lung cancer pathobiology. Increasing knowledge of molecular aberrations in lung cancer, specifically the discovery of two driver genes in pharmacologically targetable tyrosine kinases involved in growth factor receptor signalling, epidermal growth factor receptor and anaplastic lymphoma kinase, has been of major therapeutic and prognostic importance. This discovery has allowed for new, personalized approach to the management of lung cancer. Recognizing the importance of molecular signatures of lung cancer, the College of American Pathologists, International Association for the Study of Lung Cancer and Association for Molecular Pathology released the first guidelines for molecular testing in lung cancer. The introduction of minimally invasive needle techniques for the evaluation of lung cancer patients, such as endobronchial ultrasound transbronchial needle aspiration and oesophageal ultrasound-fine-needle aspiration, has revolutionized the way lung cancer patients are assessed. Samples obtained using the minimally invasive needle approaches have been shown to be sufficient not only for routine molecular testing but also for multigenic analysis. This allows bronchoscopist to assume an increasingly important role in the diagnostic workup of patients with lung cancer at all stages of the disease and contribute to personalizing the care of lung cancer 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.

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: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.390
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 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

Citations14
Published2014
Admission routes1
Has abstractyes

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