Physical and Visual Evaluation of Filters for Direct Observation of the Sun and the International Standard ISO 12312-2:2015
Bibliographic record
Abstract
Abstract We investigated the compliance of 43 commercially available solar filters (eclipse glasses) with the ISO 12312-2:2015 standard by measuring their spectral transmittances (280–2000 nm) and calculating their luminous, solar ultraviolet A, ultraviolet B, and infrared (IR) transmittances. We also evaluated the filters for usability by observing the full midday Sun and rating the view on a seven-point balanced scale, from “far too dark, details seen only with great difficulty” to “far too light, uncomfortable to view the Sun.” The mean ratings of two observers, one experienced and one inexperienced in solar observing, differed by 0.28 (95% confidence interval of the mean = 0.26). The inexperienced observer tended to be less accepting of high transmittances. All 43 solar filters complied with the UV and IR requirements. Eighteen filters passed the luminous transmittance requirements, and 24 were borderline too light or too dark. Seven of the 15 solar filters with a luminous transmittance darker than the requirement were rated as acceptable. One filter that passed and another that was borderline too light were rated as too light or far too light. The ISO 12312-2 limits derive from welding filter standards and do not represent an appropriate evidence base for direct solar viewing. This work provides the evidence base for a maximum 0.0012% and a minimum 0.00004% luminous transmittance for solar filters. The results of this study also support the use of welding filters between shades 12 and 16. Lighter welding filters are more acceptable than solar filters of the same luminous transmittance.
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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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".