Effective Target Size for the Induction of Bystander Effects in Medium Transfer Experiments
Bibliographic record
Abstract
Liu, Z., Prestwich, W. V., Stewart, R. D., Byun, S. H., Mothersill, C. E., McNeill, F. E. and Seymour, C. B. Effective Target Size for the Induction of Bystander Effects in Medium Transfer Experiments. Radiat. Res. 168, 627–630 (2007).Although radiation-induced bystander effects are frequently observed biological phenomena, the mechanism for these effects has not been fully determined. The target-hit theory and related concepts from microdosimetry provide a convenient formalism to help identify the nature of the targets responsible for initiating the emission of diffusible factors in medium transfer experiments. We used the microdosimetric models proposed by Stewart et al. (Radiat. Res. 165, 460–469, 2006) to analyze the results of published medium transfer experiments for γ-ray doses in the range of 0.04 mGy to 5 Gy. The analysis suggests that the effective size of the target responsible for initiating signal emission in HPV-G human keratinocyte donor cells is approximately 2 μm.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".