Eye-movement changes associated with a height-induced threat
Bibliographic record
Abstract
Height-related threat effects on the sensori-motor control of posture has been broadly studied; however, the effect on eye-movements during stance are less known. Kugler et al. (2014) showed that subjects susceptible to fear of heights have a more restricted gaze behavior when standing on heights compared to controls. Thus, we hypothesized that individuals will demonstrate less exploratory gaze behaviour when standing on high compared to low heights. Subjects (n=4, 1 female) were asked to stand facing towards a blank canvas for 5 minutes at 0.80 m above ground (away from the edge; Low) and 3.2 m above ground (at the edge; High) on a hydraulic lift (order counter-balanced across subjects). Eye movements were measured with the Dikablis eye tracker, and 6 QR code markers were used to define a fixed area for analysis (10.9 m2). Calibration trials (1 min) were performed after each condition to correct for offsets (along the horizontal and vertical axes) and normalize the subject's eye-level. The average standard deviation of gaze patterns along the horizontal direction was comparable; 36.9 cm in Low versus 31.3 cm in High. In contrast, the average standard deviation along the vertical direction was much smaller at Low (56.9 cm) versus High (122.5 cm). Contrary to past findings that subjects fearful of height freeze their gaze to the horizon (Kugler et al. 2014), these results indicate that individuals employ a more exploratory eye-movement pattern when standing on high heights.Acknowledgments: Acknowledgement: Funded by NSERC
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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 | 0.001 |
| 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".