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Record W2599537025 · doi:10.3389/fonc.2017.00050

Update on the Treatment of Metastatic Squamous Non-Small Cell Lung Cancer in New Era of Personalized Medicine

2017· review· en· W2599537025 on OpenAlexaff
Sara V. Soldera, Natasha B. Leighl

Bibliographic record

VenueFrontiers in Oncology · 2017
Typereview
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsEpidermal growth factor receptorEpithelial–mesenchymal transitionMedicineLung cancerCancer researchDiscoidin domainPersonalized medicineTyrosine kinaseOncologyTargeted therapyPrecision medicineLungCancerReceptor tyrosine kinaseInternal medicineBioinformaticsPathologyReceptorBiologyMetastasis

Abstract

fetched live from OpenAlex

Despite advances in molecular characterization and lung cancer treatment in recent years, treatment options for patients diagnosed with squamous cell carcinoma of the lung (SCC) remain limited as actionable mutations are rarely detected in this subtype. This article reviews potential molecular targets and associated novel agents for the treatment of advanced SCC in the era of personalized medicine. Elements of various pathways including epidermal growth factor receptor (EGFR), PI3KCA, fibroblast growth factor receptor (FGFR), retinoblastoma (Rb1), cyclin-dependent kinases (CDK), discoidin domain receptor tyrosine kinase 2 (DDR2) and mesenchymal-to-epithelial transition (MET) may play pivotal roles in the development of SCC and are under investigation for drug development.

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 score0.974
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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 head0.062
GPT teacher head0.433
Teacher spread0.372 · 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

Citations43
Published2017
Admission routes1
Has abstractyes

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