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Record W1992887025 · doi:10.1142/s0219878904000215

PSYCHOPHYSICS, SOFT-HAPTICS AND INFORMATION ACQUISITION FOR INTERNET-BASED ROBOTIC TELEOPERATION

2004· article· en· W1992887025 on OpenAlexaff
Max Q.‐H. Meng, Polley R. Liu, WILLIAM L. C. SHEK, Peter Xiao-ping Liu

Bibliographic record

VenueInternational Journal of Information Acquisition · 2004
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsTeleoperationPsychophysicsComputer scienceHaptic technologyHuman–computer interactionThe InternetRobotRoboticsTeleroboticsArtificial intelligenceSimulationPerceptionMobile robotWorld Wide WebPsychology

Abstract

fetched live from OpenAlex

This article discusses the basic ideas and the practical applications of information acquisition in relation to psychophysics theory as implemented via the Soft-Haptics concept for Internet-based robotic teleoperation systems. In specific, a study on using acoustic display for navigation applications in Internet-based robot teleoperation is presented via psychophysics tests and experimental studies of the Internet-based teleoperated robotic systems to illustrate the ideas and concepts of this paper.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.007
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations6
Published2004
Admission routes1
Has abstractyes

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