Resistance of protective gloves materials to puncture by medical needles
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
Abstract The accidental injury by medical needles, even when wearing personal protective clothing, is a growing concern for an increasing number of workers. Therefore, an effort has been undertaken to study the interaction of medical needles with materials relevant to protective gloves. A first phase of the project had investigated the influence of needle characteristics on the resistance to puncture by medical needles of selected materials relevant to protective gloves. A step-by-step analysis of the mechanism of puncture by medical needles was proposed. This second paper studies the effect of sample thickness and test conditions on the resistance to needle puncture of various types of materials relevant to protective gloves. For elastomers and fabric-reinforced elastomers, the influence of the sample thickness and needle penetration angle can be described using the principles of fracture mechanics; the non-linear relationship between puncture force and sample thickness is attributed to the elliptical shape of the fracture surface, and the effect of the needle penetration angle on puncture force is reduced to a master curve when expressed in terms of the effective sample penetration thickness. On the other hand, more textile-based materials behave as discrete media. The study of the effect of probe displacement rate and temperature seems to indicate that the needle puncture process in all studied materials is of viscoelastic nature. It was also observed that the time-temperature superposition principle applies to neoprene resistance to medical needles. These results set the basis for the design of a test method relative to the resistance of materials to medical needles. It also provides information for the development of protective gloves with improved resistance to needlesticks.
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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 | 0.002 | 0.002 |
| 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) | 0.016 | 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