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Record W1964751118 · doi:10.1017/s0263574706002955

Physiological and subjective responses to articulated robot motion

2006· article· en· W1964751118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRobotica · 2006
Typearticle
Languageen
FieldPsychology
TopicEmotion and Mood Recognition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSurpriseInferenceInference engineArtificial intelligenceComputer sciencePopulationRobotArousalPsychologyComputer visionSimulationCommunicationSocial psychologyMedicine

Abstract

fetched live from OpenAlex

This paper describes the implementation and validation of a fuzzy inference engine for estimating human affective state in real-time, using robot motions as the stimulus. The inference engine was tested with 36 subjects. To the authors' knowledge, this paper reports the first such trial that measures affective response to human-scale physical robot motions for a statistically significant population. The results demonstrate that affective state arousal can be detected using physiological signals and the inference engine. Comparison of results between the two planners shows that subjects report less anxiety and surprise with the safe planner.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.953
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.001

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 head0.037
GPT teacher head0.313
Teacher spread0.275 · 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