Bibliographic record
Abstract
ABSTRACTObjectives For this guideline, we investigated the effectiveness of radiotherapy with curative intent in medicallyinoperable patients with early-stage non-small-cell lung cancer (nsclc).Methods The guideline was developed by Cancer Care Ontario’s Program in Evidence-Based Care and by theLung Cancer Disease Site Group through a systematic review of mainly retrospective studies, expert consensus, andformal internal and external reviews.Recommendations■■ Stereotactic body radiation therapy (sbrt) with curative intent is an option that should be considered for patientswith early-stage, node-negative, medically inoperable nsclc.Qualifying Statements■■ Because of the high dose per fraction, the planning process and treatment delivery for sbrt require theuse of advanced technology to maintain an appropriate level of safety. Consistent patient positioning and4-dimensional analysis of tumour and critical structure motion during simulation and treatment deliveryare essential.■■ Preliminary results for proton-beam therapy have been promising, but the technique requires furtherclinical study.■■ Recommended fractionation schemes for sbrt should result in a biologically effective dose of 100 or greater bythe linear quadric model, choosing an α/β value of 10 [bed10(LQ) ≥ 100].Qualifying Statements■■ Because of the increased risk of treatment-related adverse events associated with centrally located tumours,consideration of tumour size and proximity to critical central structures is required when determining thedose and fractionation.■■ Examples of dose–fractionation schemes used in the included studies have been provided.■■ Based on the current evidence and the opinion of the authors, radiation doses at bed10(LQ) greater than 146might significantly increase toxicity and should be avoided.■■ Determination of the radiation bed by the linear quadratic model has limitations for the extreme hypofractionatedschemes used in sbrt.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.031 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".