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Record W2110597623 · doi:10.1109/titb.2002.802381

Behavioral avoidance dynamics in the presence of a virtual spider

2002· article· en· W2110597623 on OpenAlexaff
P. Renaud, Stéphane Bouchard, Robert Proulx

Bibliographic record

VenueIEEE Transactions on Information Technology in Biomedicine · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec en Outaouais
FundersNational Center for Research Resources
KeywordsFractalSpiderVirtual realityDynamics (music)Tracking (education)PsychologyCognitive psychologyComputer scienceHuman–computer interactionEcologyMathematicsBiology

Abstract

fetched live from OpenAlex

Tracking behavior with a virtual spider and a neutral target is compared in fearful and nonfearful subjects. Head-tracking in virtual environments appears to be a scale-free behavior with long-range fractal-like patterns. Moreover, these fractal patterns change according to what the target affords the tracker and the level of behavioral avoidance manifested by the subjects. Results are interpreted in terms of ecological psychology and nonlinear dynamics, and implications for virtual reality (VR) psychology are outlined.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.225
Teacher spread0.204 · 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

Citations57
Published2002
Admission routes1
Has abstractyes

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