Advancement in Quebec Research on the Prevention of Risks Related to Occupational Exposure to Nanomaterials
Bibliographic record
Abstract
This article includes a presentation of the research priorities and achievements of the members of this nanotoxicology researcher group in the five following themes: toxicology, epidemiology, metrology/characterization, aerodynamic behaviour/ventilation, and protective equipment. The toxicology section includes a presentation of results relating to the respiratory effects of titanium dioxide (TiO2) nanoparticles in vivo and carbon nanotubes (CNT) in vitro and in vivo. Regarding occupational exposure to nanoparticles, studies that have been carried out include evaluations of mass and number concentrations, measurements of particle size distributions, as well as electron microscopy characterization of nanometric-sized particles. In the field of protective equipment, studies are being carried out to measure the penetration of nanoparticles through protective gloves and clothing under conditions simulating their use in workplaces. Furthermore, expertise has been developed at the IRSST on the measurement of filter efficiency in ventilation systems and respiratory protective equipment. Respiratory filter efficiency performance was evaluated under constant and variable airflows. The article ends with a description of the direct impacts on nanomaterial risk prevention related to the nanotoxicology researcher group.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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".