Dose calibration of Health Canada's Fixed Point Surveillance system for environmental radiation monitoring in terms of air kerma and H*(10)
Bibliographic record
Abstract
The environmental radiation exposure in Canada has been monitored since 2002 by Health Canada's Fixed Point Surveillance network. The network consists of over eighty 7.6 cm × 7.6 cm sodium iodide spectrometers, and routinely reports to the public the environmental gamma radiation level throughout Canada. This paper describes the latest dose calibrations to air kerma and ambient dose equivalent for the future upgraded network. The calibration curves were developed using Monte Carlo techniques and further optimized via experiments in various reference fields. The dose calibration was validated over a wide range of gamma energy, dose measurement range, and angle of incidence under laboratory conditions. In environmental monitoring situations, the angular distribution of radiation exposure was analytically calculated by assuming a semi-infinite plume source, semi-infinite planar source, and infinite volume sources for the respective exposure scenarios of radioactive plume, ground contamination, and soil source. By coupling the resultant radiation angular distribution with detector's angular variation on dose response, the overall accuracy of dose measurement in each of these environmental scenarios was estimated. The accuracy is expected to be within ±3.7% for plume radiation, −5.6% for 137Cs ground contamination, and 0% to −17.1% for soil radioactive sources. The under-estimation for soil sources is mainly caused by absorption of radiation in the electronic system underneath the crystal.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".