Investigation on Circadian Action and Color Quality in Laser-Based Illuminant for General Lighting and Display
Bibliographic record
Abstract
In this work, the genetic algorithm is employed to optimize both circadian action factor (CAF) and color quality of laser-based illuminants (LBIs) with three, four, and five spectral bands to disclose its possible use in two common white lighting applications, i.e. bedroom lighting and office lighting. Comparing all LBIs at a correlated color temperature (CCT) of 3000 K and a color rendering index of 80, the CAF of four-band LBIs reaches a minimum of 0.238 and maintains at a possibly highest luminous efficacy of radiation (LER) of 422 lm/W among all cases. The performances of white LBIs are also compared with those of white light-emitting diodes (LEDs). The results demonstrate that, under the same conditions of color rendering and color temperature, both four-band LBIs and four-band LEDs exhibit the largest circadian tunability of about 4.7, while four-band LBIs possess much higher LER at the same time compared with four-band LEDs. In addition, for the display application, the investigation on the optimal circadian tunability as a function of color gamut at two CCTs (3000 K and 6500 K) is also performed. We believe that this study can serve as a useful guidance for the application of LBIs in both the healthy general lighting and display.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".