Development of an Integrative Program of Nanosafety: Promote the Coordination Between Industries and Risk Assessor
Bibliographic record
Abstract
Nanomaterials are widely present in many industrial sectors (e.g., chemical, biomedical, environment), and their application is expected to significantly expand in the coming years. However, nanomaterial use raises many questions about the potential risks to human health and the environment and, more specifically, to occupational health. The available literature supports the ability of the lung, gastrointestinal tract, and skin to act as significant barriers against systemic exposure to many nanomaterials. However, because a potential risk issue exists about the toxicity of nanomaterials to the biological material, tools need to be developed for improving the risk management of the regulators. The goal is to develop a tool that examines the current knowledge base regarding the health risks posed by engineered nanoparticles to improve nanotechnology safety prior to the marketing phase. The approach proposed during this work was to establish a safety assessment constructed on a decision-control pathway regarding nanomaterial production and consumer's product to integrate different aspects. These aspects include: (1) primarily research and identification of the nanomaterial base of physicochemical properties, toxicity, and application; (2) the occupational exposure risk during the manufacturing process; (3) and the engineered nanomaterial upon the consumer product. This approach provides important parameters to reduce the uncertainty related to the production of nanomaterials prior their commercialization, reduce the reluctance from the industry, and provide a certification tool of sanitary control for the regulators. This work provides a better understanding of a critical issue of nanomaterials and consumer safety.
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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 | 0.044 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".