Insight gained from responses to surveys on reference dosimetry practices
Bibliographic record
Abstract
PURPOSE: To present the results and discuss potential insights gained through surveys on reference dosimetry practices. METHODS: Two surveys were sent to medical physicists to learn about the current state of reference dosimetry practices at radiation oncology clinics worldwide. A short survey designed to maximize response rate was made publicly available and distributed via the AAPM website and a medical physics list server. Another, much more involved survey, was sent to a smaller group of physicists to gain insight on detailed dosimetry practices. The questions were diverse, covering reference dosimetry practices on topics like measurements required for beam quality specification, the actual measurement of absorbed dose and ancillary equipment required like electrometers and environment monitoring measurements. RESULTS: There were 190 respondents to the short survey and seven respondents to the detailed survey. The diversity of responses indicates nonuniformity in reference dosimetry practices and differences in interpretation of reference dosimetry protocols. CONCLUSIONS: The results of these surveys offer insight on clinical reference dosimetry practices and will be useful in identifying current and future needs for reference dosimetry.
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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 | 0.032 | 0.157 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".