Update on the IEC 60825-13 technical report on laser radiation measurements and the ANSI Z136.4 recommended practice for laser safety measurements for hazard evaluation
Bibliographic record
Abstract
The International Electrotechnical Commission (IEC) 60825-13 Technical Report on Laser Radiation Measurements is being prepared as a new committee draft. The group responsible for developing this Technical Report is Working Group (WG) 3 of the IEC Technical Committee 76. WG 3 membership includes representatives from Australia, Austria, Finland, Germany, Italy, Japan, Romania, Sweden, Switzerland, the United Kingdom, and the United States. IEC 60825-13 is intended to be used as a guide for making radiometric measurements of laser and LED radiation levels for comparison with the AELs and MPEs in IEC 60825-1. The American National Standards Institute (ANSI) Z136.4 Recommended Practice for Laser Safety Measurements for Hazard Evaluation has passed subcommittee and is in committee draft for vote form. Current membership working on the Z136.4 document includes the National Institute of Standards and Technology, the Food and Drug Administration, the Department of Defense, Industry, Professional Societies, the Canadian Department of Defense, and the UK’s National Radiological Protection Board. Z136.4 is intended to provide guidance for measurement procedures used for classification and hazards evaluation of lasers to manufacturers, Laser Safety Officers (LSOs), and trained laser users.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 0.041 |
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".