Action strategies of individuals during aperture crossing in nonconfined space
Bibliographic record
Abstract
Walking through cluttered environments is a requirement of everyday locomotion, and individuals will walk toward open space and adjust their actions in order to prevent injury. When walking in a confined space, individuals require a shoulder rotation to pass through apertures smaller than 1.3 times their shoulder widths. The current study aimed to identify the action strategies employed by young adults to avoid contacting two obstacles placed in the travel path when walking in a nonconfined space. Participants (N = 12) walked along a 10-m path towards a goal while avoiding two vertical obstacles specifically placed to create an aperture (of 0.6 to 1.8 times the participants' shoulder widths) on opposite sides of the travel path midline. Results showed that participants walked around obstacles that were separated by less than 1.4 times their shoulder width (i.e., critical point). When participants deviated from their initial travel path, they did so by maintaining a consistent protective zone, regardless of the aperture width. The protective zone had dimensions of 3.80 m in the plane of progression and of 0.30 m between themselves and the obstacles at the time of crossing. This study demonstrates that individuals use body-scaled information to control actions in nonconfined space similar to that used in confined space.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".