Bibliographic record
Abstract
Fusion research and tritium removal facilities potentially handle large inventories of tritium gas (HT). If any HT is released into the workplace, a fraction may be converted to tritiated water vapour (HTO). A convenient method to determine the activity concentration of each species is necessary to assess the potential hazard since the radiological hazard of HTO is more than 104 that due to HT. Passive samplers for measuring tritiated water vapour (HTO) have been shown to be suitable for use indoors and outdoors. These simple samplers consist of a standard 20-mL liquid scintillation vial with a diffusion orifice that determines the sampling rate.The total tritium samplers described herein are passive or diffusion samplers that contain a small amount of AECL-proprietary wet-proofed catalyst fixed to the underside of the sampling heads to allow conversion of the HT to HTO that is subsequently collected in the sink, (HTO), in the bottom of the sampler. After an appropriate sampling time, liquid scintillation cocktail is added to the vial and the activity collected determined by liquid scintillation analysis. When used in conjunction with the conventional HTO passive sampler the difference between the total and HTO samplers can be used to determine the HT fraction ((HT+HTO) - HTO HT). The sampling rates for the modified diffusion sampler were measured to be 4.6 and 8.1 L/d for HTO and HT, respectively. For a fifteen-minute sampling period, passive samplers can be used to measure tritium activity concentrations from 37 kBq/m3 to 115 MBq/m3.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".