Bibliographic record
Abstract
ABSTRACT: Purpose. To study the effect of coatings on the resistance of CR‐39 industrial plano lenses to ballistic impacts and abrasion from fine particles. Methods. Twelve groups of CR‐39 lenses with various scratch‐resistant (SR) or combinations of scratch‐resistant and antireflective (SR‐AR) coatings were mounted in metal industrial spectacle frames. The ZEST protocol was used to determine the mean impact speed for breakage of each lens group using the Canadian Standards Association ballistic test protocol. One pair of lenses from each group was tested for abrasion resistance using the falling sand method. Abrasion resistance was ranked by the degree of haze observed by three independent observers. Results. Uncoated lenses had the best impact resistance and worst abrasion resistance. SR‐coated lenses showed mild to moderate reductions in impact resistance, with no correlation between impact and abrasion resistance. SR‐AR‐coated lenses had very good abrasion resistance, but severely reduced impact resistance. Conclusions. Most SR‐coated CR‐39 lenses have a high probability of meeting the high‐velocity impact resistance requirement of industrial lenses, whereas CR‐39 lenses with SR‐AR coats are too fragile to be used in industrial spectacles. As a group, the SR‐AR coating tended to be more resistant to abrasion by fine particles and less resistant to ballistic impacts, but the abrasion resistance of the SR‐coated lenses was more variable, and, thus, overall there was no significant correlation between impact resistance and abrasion resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".