Measuring Customers' Perceived Service Quality in Hotel Industry
Bibliographic record
Abstract
Synchronizing gait to music-based auditory cues (rhythmic auditory stimulation) is a strategy used to manage gait impairments in a variety of neurological conditions, including Parkinson's disease. However, knowledge of how to individually optimize music-based cues is limited. The purpose of this study was to investigate how instructions to synchronize with auditory cues influences gait outcomes among healthy young adults with either good or poor beat perception ability. 65 healthy adults walked to metronome and musical stimuli with high and low levels of perceived groove (how much it induces desire to move) and familiarity at a tempo equivalent to their self-selected walking pace. Participants were randomized to instruction conditions: (i) synchronized: match footsteps with the beat, or (ii) free-walking: walk comfortably. Participants were classified as good or poor beat perceivers using the Beat Alignment Test. In this study, poor beat perceivers show better balance-related parameters (stride width and double-limb support time) when they are not instructed to synchronize their gait with cues (versus when synchronization was required). Good beat perceivers, in contrast, were better when instructed to synchronize gait (versus when no synchronization was required). Changes in stride length and velocity were influenced by musical properties, in particular the perceived 'groove' (greater stride length and velocity with high- versus low-groove cues) and, in some cases, this interacted with beat perception ability. The results indicate that beat perception ability and instructions to synchronize indeed influence spatiotemporal gait parameters when walking to music- and metronome-based rhythmic auditory stimuli. Importantly, these results suggest that both low groove cues and instructing poor beat perceivers to synchronize may interfere with performance while walking, thus potentially impacting both empirical and clinical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".