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Record W2972480122 · doi:10.21037/tlcr.2019.09.05

Pathologic response after modern radiotherapy for non-small cell lung cancer

2019· review· en· W2972480122 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTranslational Lung Cancer Research · 2019
Typereview
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsCentre Hospitalier de l’Université de MontréalHealth Sciences CentreSunnybrook Health Science CentreUniversité de Montréal
Fundersnot available
KeywordsMedicineLung cancerRadiation therapyOncologyRadiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

In non-small cell lung cancer (NSCLC), pathologic complete response (pCR) following radiotherapy treatment has been shown to be an independent prognostic factor for long-term survival, progression-free survival and locoregional control. PCR is considered a surrogate to therapeutic efficacy, years before survival data are available, and therefore can be used to guide treatment plans and additional therapeutic interventions post-surgical resection. Given the extensive fibrotic changes induced by radiotherapy in the lung, radiological assessment of response can potentially misrepresent pathologic response. The optimal timing for assessment of pathologic response after conventionally fractionated radiotherapy and stereotactic ablative radiotherapy (SABR) remains poorly understood. In this review, we summarize recent literature on pathologic response after radiotherapy for early stage and locally advanced NSCLC, we discuss current controversies around radiobiological considerations, and we present upcoming trials that will provide insight into current knowledge gaps.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.119
GPT teacher head0.479
Teacher spread0.360 · 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