MétaCan
Menu
← Back to cohort
Record W2569662783 · doi:10.1167/16.12.1365

The effects of a human confederate and goal location on the path selection of young adults

2016· article· en· W2569662783 on OpenAlexaff
Lana M. Pfaff, Michael E. Cinelli

Bibliographic record

VenueJournal of Vision · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPath (computing)ObstacleTrajectoryPosition (finance)Computer scienceSelection (genetic algorithm)MathematicsGeometryPsychologyPhysicsGeographyArtificial intelligence

Abstract

fetched live from OpenAlex

INTRODUCTION: The behavioural dynamics model suggests that obstacles correspond to repellers forcing trajectories to diverge, whereas goals act as attractors in which path trajectory converges. However, environmental obstacles are avoided based on characteristics; path trajectories are wider for animate compared to inanimate objects. Nonetheless, the effects of different obstacle properties (animate vs. inanimate) on repulsion forces are unclear. The purpose of this study was to determine whether the attraction of a goal dominates path selection despite obstacle characteristics. METHODS: Participants (N=15) were instrumented with IRED markers (NDI Optotrak) on the head and trunk to calculate the location of the Centre of Mass (COM) over time. Participants were instructed to walk along a 10m path toward a goal located at one of three possible locations: 1) midline of the pathway; 2) 80cm to left of midline; or 3) 80cm to right of midline. Halfway along the pathway three obstacles were placed perpendicular to the pathway consisting of either three vertical poles (20cm diameter) or two vertical poles and a confederate. The obstacles were each separated by 80cm, creating two equal apertures on either side of the midline. The location of the confederate was either: 1) along midline; 2) 80cm to left of midline; 80cm to right of midline; or 4) not present. RESULTS: A stepwise multiple regression analysis was used to test if gender, shoulder width, confederate location, and goal location significantly predicted participants' path selection (i.e., medial-lateral position of COM at time of crossing the obstacles). The results of the regression indicated that goal location explained 48.9% of the variance (R2=.489, F(1,175)=170.6,p< .001) in path selection (β = .700, p< .001). CONCLUSION: The findings suggest that different obstacle characteristics (animate vs. inanimate) do not affect repulsion but rather the attraction of the goal is what dominates one's path. Meeting abstract presented at VSS 2016

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.008
GPT teacher head0.290
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vision→Same topicUrban Transport and Accessibility→French-language works237,207→