P126 A task-based silica exposure modelling tool for construction companies
Bibliographic record
Abstract
In collaboration with an industry safety association (British Columbia Construction Safety Alliance) and the local regulator (WorkSafeBC) we developed a web-based modelling tool that is intended to help OHS personnel with quantitative risk assessment to respirable crystalline silica (RCS) on construction worksites. The exposure estimates are derived from a multiple linear regression model that was constructed using a database of 4550 task-based RCS exposure measurements. The database comprised data from peer-reviewed and grey literature, data shared from industry, and 318 field measurements collected at construction sites in 2015. The variable nature of construction work necessitated the use of a task-based, rather than job-based model. The model estimates uncontrolled exposure for 47 silica-generating tasks, and exposure levels anticipated following standard engineered control interventions. Uncertainty is also calculated and conveyed. The other variables in the model are: work environment (indoor vs. outdoor), sampling duration, activity sector (e.g. residential, commercial), project type (e.g. new construction, renovation), use of engineering controls, and region. If controlled exposures are above the exposure limit the tool provides advice on respiratory protection selection. The tool outputs a formal RCS “exposure control plan” with further information on administrative controls that should be followed to minimise exposures. Where insufficient data are available, users are advised to collect exposure measurements; they will be encouraged to share data to allow the model to be continually updated. Despite the challenges of estimating exposure in variable construction settings, this tool has several potential benefits: i) education of construction employers and employees on RCS hazards and control effectiveness; ii) a method of quantitative exposure-based risk assessment that can be used by non-expert users; iii) a model for ongoing exposure data measurement collection and analysis; and iv) a potential for continual improvement in risk reduction (as new controls are assessed and added to the database.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.012 |
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".