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Record W3083480767 · doi:10.1016/j.ctro.2020.08.005

Stereotactic radiosurgery (SRS) – A new normal for small cell lung cancer?

2020· review· en· W3083480767 on OpenAlexaff
Ian Pereira, Ben J. Slotman, Chad G. Rusthoven, Matthew S. Katz, Richard Simcock, Hina Saeed

Bibliographic record

VenueClinical and Translational Radiation Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsRadiosurgeryMedicineLung cancerRadiation therapyOncologyLungCancerSmall Cell Lung CarcinomaInternal medicineRadiologySmall-cell carcinoma

Abstract

fetched live from OpenAlex

Small cell lung cancer (SCLC) outcomes remain poor. Approximately, 40–60% of SCLC patients develop brain metastases (BMs) [1–3] and less than 15% survive beyond two years [4,5]. In lung cancer management, contemporary advances in systemic therapies and focal radiation techniques have also tended to improve outcomes more in non-small cell lung cancer (NSCLC) than SCLC over the last decade [4]. For patients with brain metastases, whereas upfront SRS has become the preferred treated for limited brain metastases arising from most solid tumor histologies [6], whole brain radiotherapy (WBRT) remains the standard of care for SCLC [7].

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.159
GPT teacher head0.504
Teacher spread0.345 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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