Probabilistic exposure assessment of operator and residential exposure; a Canadian regulatory perspective. Annals of Occupational Hygiene 45(90001): 43S-447
Bibliographic record
Abstract
An overview of the considerations central to selection of probabilistic versus deterministic approaches to assessment of operator and residential exposure are provided. From a regulat-ory perspective, the decision to use probabilistic over deterministic assessments should include consideration of factors such as the nature of the populations being assessed, includ-ing the expected duration and frequency of their exposures, as well as an understanding of the toxicity endpoints that the exposure assessment will be linked to during risk assessment. In situations where there is an identifiable need to characterize variability and uncertainty and/or quantify the exposure that will represent most of the exposed population, and where there are adequate data to characterize input parameters, probabilistic assessments may be appropriate. Issues with respect to probabilistic assessments for which detailed, harmonized guidance are required are outlined. These issues are discussed within the context of a tiered approach to exposure and risk assessment. 2001 British Occupational Hygiene Society.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".