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Touch Noise Increases Vibrotactile Sensitivity in Old and Young

2005· article· en· W2080209735 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

VenuePsychological Science · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
Topicstochastic dynamics and bifurcation
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
Fundersnot available
KeywordsStochastic resonanceSubthreshold conductionCounterintuitiveNoise (video)Sensitivity (control systems)PsychologySensory thresholdSensory systemAudiologySIGNAL (programming language)Detection theoryPsychophysicsEnergy (signal processing)CommunicationPhysical medicine and rehabilitationCognitive psychologyPerceptionComputer scienceNeuroscienceArtificial intelligencePhysicsMedicineMathematicsEngineeringTelecommunicationsStatisticsElectrical engineering

Abstract

fetched live from OpenAlex

Stochastic resonance (SR) occurs when the detection of a subthreshold signal is aided by the presence of random energy fluctuations in the signal modality, commonly called noise. SR is counterintuitive because such noise usually worsens performance. Nonetheless, SR has been demonstrated both theoretically and experimentally in human sensory systems. Using a psychophysically sophisticated paradigm, we show that SR aids the detection of vibrating touch stimuli presented to the foot soles of both healthy elderly people with elevated vibrotactile thresholds and healthy young people with normal vibrotactile thresholds. The results also suggest that it is possible to know a priori the amount of noise needed for optimal SR effects given the degree to which the signal is subthreshold. Thus, SR may be practical as a rehabilitative aid for individuals with elevated sensory thresholds.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.198

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)0.0000.000

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 head0.011
GPT teacher head0.299
Teacher spread0.288 · 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