The Impact of Sound in Modern Multiline Video Slot Machine Play
Bibliographic record
Abstract
Slot machine wins and losses have distinctive, measurable, physiological effects on players. The contributing factors to these effects remain under-explored. We believe that sound is one of these key contributing factors. Sound plays an important role in reinforcement, and thus on arousal level and stress response of players. It is the use of sound for positive reinforcement in particular that we believe influences the player. In the current study, we investigate the role that sound plays in psychophysical responses to slot machine play. A total of 96 gamblers played a slot machine simulator with and without sound being paired with reinforcement. Skin conductance responses and heart rate, as well as subjective judgments about the gambling experience were examined. The results showed that the sound influenced the arousal of participants both psychophysically and psychologically. The sound also influenced players' preferences, with the majority of players preferring to play slot machines that were accompanied by winning sounds. The sounds also caused players to significantly overestimate the number of times they won while playing the slot machine.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".