Proposal and practicality of an alternative blue-light hazard risk assessment method for high-intensity white-light sources at workplaces
Bibliographic record
Abstract
Objective. It is prescribed to determine BLH weighted radiances, LB, for an assessment of spotlights with an angular subtense α≥11mrad. The BLH weighted irradiance, EB, can be used alternatively for smaller sources. Appropriate instruments are not common among persons commissioned with risk assessment (RA), and especially LB measurements may be challenging. Therefore, a practical BLH RA approach is proposed that is based on illuminance, Ev, pre-calculated blackbody BLH efficacies of luminous radiation, KB,vPlanck, and solid angle considerations. Methods. The practicality of this method was examined and compared against other RA approaches. Results. To ensure comparability of the applied instruments, measurements were performed close to a radiance standard, showing deviations within the lamp's expanded uncertainties (<4%), whereas the deviations were ±15% for longer distances. Focusing on a complex LED spotlight, all detected values could be converted to LB by means of the RA methods within ±20%. Two field tests with several spotlights yielded maximum permissible exposure durations obtained from the different RA approaches that agreed among each other within uncertainties largely below ±30%. Conclusion. The general practicality of the proposed Ev method can be concluded for a workplace BLH RA of white-light sources.
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 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".