Cutting Fluids Usage and Impacts in Metal Workshops in Ibadan, Southwestern Nigeria
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
This paper presents a report on cutting fluids utilization and its impacts on workers in machining workshops in Ibadan, Nigeria.The major users of cutting fluids and their workshops were identified.It was found that there are 103 operating metal workshops in Ibadan and these workshops are located within seven local government areas of the city.Out of the total number, 85 are in fabrication, 39 are in crankshaft operations and 32 are engaged in block boring operations.The type and consumption of cutting fluids, coolant delivery techniques, length of use before disposal, disposal methods, and monitoring maintenance were studied.The results indicated that the most used cutting fluid is soluble oil with average total consumption of 402 litres monthly.The pouring of spent cutting fluids on the ground is the most adopted disposal method.Research on occupation exposures to cutting fluids has suggested that machine operators in metal cutting are at high risk of developing cancer, allergenic disorders, and lung diseases.Results obtained also showed that less than 22% of machine operators were aware of occupational hazards.Few of the operators (23%) wore safety devices/clothing, and health and safety standards were neither practiced nor enforced.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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