Characterization of the Resistance of Protective Gloves to Pointed Blades
Bibliographic record
Abstract
Hand lacerations account for a large percentage of occupational injuries. Wearing appropriate protective gloves has been shown to reduce these risks. However, the case of pointed blades, which include knife tips, metal sharps, and a large number of cutting tools, is still largely unexplored and calls for more research. This paper presents some initial results of tests performed with glove materials and several types of pointed blades used as a puncture probe. Tested glove materials include uncoated and polymer-coated Kevlar and Dyneema knits, leather as well as sheets of neoprene, nitrile rubber, and polyurethane. The effect of various parameters such as blade reuse, sample thickness, blade tip angle, probe displacement rate, blade lubrication, and sample support on the resistance of these materials to pointed blades was studied. The results show that the maximum force appears to increase in a non-linear way with the thickness of the membrane. A decrease in puncture force with decreasing tip angle was observed with all materials. In addition, measurements carried out at displacement rates between 1 and 500 mm/min eventually reveal in some instances the possible existence of two puncture regimes. Finally, the contribution of both friction and sample deformation on the pointed blade puncture process is evidenced by the large effect of lubrication and sample support on the maximum force. However, no correlation appears to exist between resistance to pointed blades and resistance to cutting or puncture measured with standard test methods. This demonstrates the need for more research in that area and ultimately a dedicated standard test method.
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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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".