Comfort and performance of power line maintainers' gloves during electrical utility work in the cold
Bibliographic record
Abstract
BACKGROUND: Electrical utility workers wear thick rubber gloves and often work in the cold. OBJECTIVE: To document the challenge of working in the cold and the effectiveness of different glove/liner combinations in keeping workers' hands warm. METHODS: Ten experienced male electrical utility employees worked in a controlled temperature walk-in chamber at -20 °C for 45 minutes for each of five glove conditions: standard five-finger rubber gloves with cotton liners and gauntlets, mitten style gloves, a prototype wool liner, and two heating options; glove or torso. Dependent measures were maximum grip force, skin temperatures, finger dexterity and sensitivity to touch, ratings of perceived effort and a rating of thermal sensation. RESULTS: Participants' hand skin temperatures decreased, they perceived their hands to be much colder, their finger sensitivity decreased and their ratings of perceived exertion increased, however their performance did not degrade over the 45 minute trials. The mitten-style gloves showed a smaller drop in skin temperature for the 3rd and 5th digits (p< 0.05) than the other glove conditions. CONCLUSIONS: Mitten style gloves kept workers' hands warmer than the standard five finger glove.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".