Effects of machining conditions on specific surface of PM<sub>2.5</sub> emitted during metal cutting
Bibliographic record
Abstract
Indoor air quality has become an important matter for health and safety. Most manufacturing processes generate aerosols. In the metal cutting industry, dry machining processes are accompanied by dust emission (fogs, fine chips and metallic dust in both micrometers and nanometers scales) that has impacts on workers’ health. This research work aimed to understand and reduce the harmful impacts of the machining process on the occupational safety. In this study, an experimental investigation was carried out on fine and ultrafine metallic dust emission during slot milling of 2024-T351, 6061-T6 and 7075-T6 aluminum alloy in dry conditions. It was confirmed that the cutting conditions influence significantly the specific surface area of ultrafine particles. It was also found that the cutting speed is a determinant factor for specific surface area of ultrafine particles and control during the slot milling process.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".