Calculations for plane-parallel ion chambers in 60Co beams using the EGSnrc Monte Carlo code
Bibliographic record
Abstract
The EGSnrc Monte Carlo simulation system is used to obtain, for 10 plane-parallel ionization chambers in 60Co beams, the correction factors Kcomp and Pwall that account for the nonequivalence of the chamber wall material to the buildup cap and the phantom material, respectively. A more robust calculation method has been used compared to that used in previous works. A minor conceptual error related to the axial nonuniformity correction factor, Kan, has been identified and shown to have an effect of about 0.2%. The assumption that Pwall in-phantom is numerically equal to Kcomp calculated for a water buildup cap is shown to be accurate to better than 0.06%, thereby justifying the use of Kcomp calculations which are much more efficient. The effect on the calculated dose to the air in the cavity of the particle production threshold and transport energies used in the simulations is studied. Uncertainties in the calculated correction factors due to uncertainties in the photon and electron cross-section data are studied. They are 0.14% and 0.24%, respectively (1 standard deviation), for Kcomp factors. The uncertainties on Kwall factors are 0.03% from photon cross-section uncertainties and negligible from electron cross-section uncertainties. A comparison with previous EGS4/PRESTA calculations shows that present results are systematically higher by an average of 0.8%, ranging from 0.4% up to 1.4%. The present results are in better agreement with reported experimental values.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".