luox: an open-source, open-access web platform implementing international standards for the quantification of light
Bibliographic record
Abstract
Light exposure is not only important for seeing the world around us, it is also a key driver for health and well-being. The quantification of light, particularly in parameters relevant for humans, is subject to international consensus documents developed by the International Commission on Illumination (abbreviated as CIE = Commission Internationale de l’Eclairage). This includes quantities for the intensity of light exposure (e.g., illuminance, measured in lux) or indices of how well a light source renders colours (e.g., Rf). The CIE provides various spreadsheet-based tools for calculating these quantities from spectral measurements of radiant energy. Here, we present and discuss the open-source and open-access web platform luox, which was developed with researchers in mind to simplify the process of calculating relevant aspects of light exposures in experiments with human participants. We specifically focus on the challenges of translating written documents and equations into a web based platform using ES6 and ReactJS.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.079 | 0.065 |
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".