Resistance of protective gloves materials to puncture by medical needles
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".