DETECTION OF THE STROBOSCOPIC EFFECT UNDER LOW LEVELS OF THE STROBOSCOPIC VISIBILITY MEASURE
Bibliographic record
Abstract
Cyclic variations in lighting system luminous flux, known as temporal light modulation (TLM), may have visual, neurobiological, and performance and cognition effects on viewers.Researchers have derived a Stroboscopic Visibility Measure (SVM) to characterize the TLM signal in a manner that is thought to predict the visibility of the stroboscopic effect.An SVM of 1 means that the average person would detect the phenomenon 50% of the time.If there exists a broad range of visual sensitivity in the general population, setting a limit based on the average person might lead to an unacceptable risk of an adverse consequence for the most sensitive individuals.There is an absence of published data concerning the relationship of SVM to stroboscopic visibility among the general population.This experiment was conducted to provide such data, using commercially available lamps to provide a range of SVM conditions (SVM: 0; 0.4-0.6;1.0; 1.6; and >2.0).
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".