Three discipline collaborative radiation therapy (3DCRT) special debate: Peer review in radiation oncology is more effective today than 20 years ago
Bibliographic record
Abstract
Radiation Oncology is a highly multidisciplinary medical specialty, drawing significantly from three scientific disciplinesmedicine, physics, and biology.As a result, discussion of controversies or changes in practice within radiation oncology must involve input from all three disciplines.For this reason, significant effort has been expended recently to foster collaborative multidisciplinary research in radiation oncology, with substantial demonstrated benefit.[1][2][3] In light of these results, we endeavor here to adopt this "team-science" approach to the traditional debates featured in this journal.This article is part of a series of special debates entitled "Three Discipline Collaborative Radiation Therapy (3DCRT)" in which each debate team includes a radiation oncologist, medical physicist, and radiobiologist.We hope that this format will not only be engaging for the readership but will also foster further collaboration in the science and clinical practice of radiation oncology.
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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 | 0.182 | 0.503 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.013 | 0.030 |
| Scholarly communication | 0.035 | 0.033 |
| Open science | 0.007 | 0.017 |
| Research integrity | 0.029 | 0.026 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
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".