Models for Evaluating Agents Intended for the Prophylaxis, Mitigation and Treatment of Radiation Injuries Report of an NCI Workshop, December 3–4, 2003
Bibliographic record
Abstract
Stone, H. B., Moulder, J. E., Coleman, C. N., Ang, K. K., Anscher, M. S., Barcellos-Hoff, M. H., Dynan, W. S., Fike, J. R., Grdina, D. J., Greenberger, J. S., Hauer-Jensen, M., Hill, R. P., Kolesnick, R. N., MacVittie, T. J., Marks, C., McBride, W. H., Metting, N., Pellmar, T., Purucker, M., Robbins, M. E., Schiestl, R. H., Seed, T. M., Tomaszewski, J., Travis, E. L., Wallner, P. E., Wolpert, M. and Zaharevitz, D. Models for Evaluating Agents Intended for the Prophylaxis, Mitigation and Treatment of Radiation Injuries. Report of an NCI Workshop, December 3–4, 2003. Radiat. Res. 162, 711–728 (2004).To develop approaches to prophylaxis/protection, mitigation and treatment of radiation injuries, appropriate models are needed that integrate the complex events that occur in the radiation-exposed organism. While the spectrum of agents in clinical use or preclinical development is limited, new research findings promise improvements in survival after whole-body irradiation and reductions in the risk of adverse effects of radiotherapy. Approaches include agents that act on the initial radiochemical events, agents that prevent or reduce progression of radiation damage, and agents that facilitate recovery from radiation injuries. While the mechanisms of action for most of the agents with known efficacy are yet to be fully determined, many seem to be operating at the tissue, organ or whole animal level as well as the cellular level. Thus research on prophylaxis/protection, mitigation and treatment of radiation injuries will require studies in whole animal models. Discovery, development and delivery of effective radiation modulators will also require collaboration among researchers in diverse fields such as radiation biology, inflammation, physiology, toxicology, immunology, tissue injury, drug development and radiation oncology. Additional investment in training more scientists in radiation biology and in the research portfolio addressing radiological and nuclear terrorism would benefit the general population in case of a radiological terrorism event or a large-scale accidental event as well as benefit patients treated with radiation.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".