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Record W3018187588 · doi:10.1109/toh.2020.2990712

A Review of Surface Haptics: Enabling Tactile Effects on Touch Surfaces

2020· article· en· W3018187588 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Haptics · 2020
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsÉcole de Technologie Supérieure
FundersCentre National de la Recherche ScientifiqueNatural Sciences and Engineering Research Council of CanadaTürkiye Bilimsel ve Teknolojik Araştırma Kurumuİslam Tarih, Sanat ve Kültür Araştırma Merkezi
KeywordsHaptic technologyTactile perceptionTactile sensorTactile displaySurface (topology)Tactile stimuliPerception

Abstract

fetched live from OpenAlex

In this article, we review the current technology underlying surface haptics that converts passive touch surfaces to active ones (machine haptics), our perception of tactile stimuli displayed through active touch surfaces (human haptics), their potential applications (human-machine interaction), and finally, the challenges ahead of us in making them available through commercial systems. This article primarily covers the tactile interactions of human fingers or hands with surface-haptics displays by focusing on the three most popular actuation methods: vibrotactile, electrostatic, and ultrasonic.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.294
Teacher spread0.237 · 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