Ion chamber absorbed dose calibration coefficients, <i>N</i><sub><i>D</i>,<i>w</i></sub>, measured at ADCLs: Distribution analysis and stability
Bibliographic record
Abstract
PURPOSE: To analyze absorbed dose calibration coefficients, ND,w, measured at accredited dosimetry calibration laboratories (ADCLs) for client ionization chambers to study (i) variability among ND,w coefficients for chambers of the same type calibrated at each ADCL to investigate ion chamber volume fluctuations and chamber manufacturing tolerances; (ii) equivalency of ion chamber calibration coefficients measured at different ADCLs by intercomparing ND,w coefficients for chambers of the same type; and (iii) the long-term stability of ND,w coefficients for different chamber types by investigating repeated chamber calibrations. METHODS: Large samples of ND,w coefficients for several chamber types measured over the time period between 1998 and 2014 were obtained from the three ADCLs operating in the United States. These are analyzed using various graphical and numerical statistical tests for the four chamber types with the largest samples of calibration coefficients to investigate (i) and (ii) above. Ratios of calibration coefficients for the same chamber, typically obtained two years apart, are calculated to investigate (iii) above and chambers with standard deviations of old/new ratios less than 0.3% meet stability requirements for accurate reference dosimetry recommended in dosimetry protocols. RESULTS: It is found that ND,w coefficients for a given chamber type compared among different ADCLs may arise from differing probability distributions potentially due to slight differences in calibration procedures and/or the transfer of the primary standard. However, average ND,w coefficients from different ADCLs for given chamber types are very close with percent differences generally less than 0.2% for Farmer-type chambers and are well within reported uncertainties. CONCLUSIONS: The close agreement among calibrations performed at different ADCLs reaffirms the Calibration Laboratory Accreditation Subcommittee process of ensuring ADCL conformance with National Institute of Standards and Technology standards. This study shows that ND,w coefficients measured at different ADCLs are statistically equivalent, especially considering reasonable uncertainties. This analysis of ND,w coefficients also allows identification of chamber types that can be considered stable enough for accurate 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".