Effect of heterogeneity in radiosensitivity on LQ based isoeffect formalism for low α/β cancers
Bibliographic record
Abstract
Change of fractionation for external beam radiation therapy based on linear-quadratic (LQ) formalism assumes that a single alpha/beta is sufficient to characterize tumour response to dose fractionation. In reality, both inter-patient and intra-tumour heterogeneity might affect the applicability of isoeffectiveness formalism. The impact of heterogeneity on recently proposed hypofractionation schemes for the prostate has been analysed. The alpha/beta ratio was assumed to be Gaussian distributed with a mean value of 1.5 Gy. Gaussian and lognormal distributions for alpha were modelled. TCP model parameters were adjusted to lead to TCP = 0.80 for 70 Gy at 2 Gy per fraction. TCP loss from heterogeneity and doses required to restore TCP = 0.80 were calculated. The effect of heterogeneity was moderate. Doses to restore TCP = 0.80 in most cases were less than 1 Gy. The largest TCP loss was 4%. The difference between predictions of single alpha/beta and heterogeneity models is too small to be detected in a clinical trial.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".