Nanotechnology risks: A 10-step risk management model in nanotechnology projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use and handling of par- ticulate material between 1 and 100 nm, also known as nanotechnology, has been shown to have potential to revolution- ize many aspects of industries, medical practices and the human environment. However, very little is known about the risks and hazards of nanomaterials to humans and the environment, so a con- servative approach is encouraged. This article proposes a 10- step qualitative risk management model for nanotechnology project managers, which enables them to detect significant risks in a systematic approach and provide decisions and suit- able actions regarding the health of their employees. INTRODUCTION The properties of mate- rials at atomic and molecular size range (between 1 and 100 nm) are significantly different from those at a larger scale. This emerging technology is based on the size and surface condition of solid par- ticles 1,2
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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 it