Radiation Biology in the Context of Changing Patterns of Radiotherapy
Bibliographic record
Abstract
The last decade has witnessed a revolution in the clinical application of high-dose "ablative" radiation therapy. Initially this approach was limited to the treatment of brain tumors, but more recently we have seen its successful extension to tumors outside the brain, e.g., for small lung nodules. These advances have been driven largely by improvements in image-guided inverse treatment planning that allow the dose per fraction to the tumor to be increased over the conventional 2 Gy dose while keeping the late normal tissue complications at an acceptable level by dose limitation. Despite initial concerns about excessive late complications, as might be expected based on dose extrapolations using the linear-quadratic equation, these approaches have shown considerable clinical promise. Our knowledge of the biological consequences of high-doses of ionizing radiation in normal and cancerous tissues has lagged behind these clinical advances. Our intent here is to survey recent experimental findings from the perspective of better understanding the biological effects of high-dose therapy and whether they are truly different from conventional doses. We will also consider the implications of this knowledge for further refining and improving these approaches on the basis of underlying mechanisms.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".