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Record W2140155664 · doi:10.1142/s0219477504001616

PSYCHOPHYSICS OF STOCHASTIC RESONANCE

2004· article· en· W2140155664 on OpenAlexaff
Lawrence M. Ward

Bibliographic record

VenueFluctuation and Noise Letters · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
Topicstochastic dynamics and bifurcation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStochastic resonancePsychophysicsComputer scienceNoise (video)Information processingDetection theoryStatistical physicsCognitive scienceArtificial intelligencePerceptionPsychologyPhysicsCognitive psychologyNeuroscienceTelecommunications

Abstract

fetched live from OpenAlex

Although stochastic resonance has been demonstrated for many physical and biological systems, in both dynamic and threshold forms, its study in whole human beings presents special problems. Psychophysics provides theoretical and methodological tools for measuring information processing by humans, but modern psychophysics seems to be incompatible with some of the concepts of current theories of stochastic resonance. In this paper I review some of these problems, providing suggestions for solutions where none have as yet appeared. In particular, I discuss incompatibilities between signal detection theory and threshold stochastic resonance, and the problem of the effect of noise on information transfer across a "soft" threshold.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.271

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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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 designTheoretical or conceptual
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

Citations27
Published2004
Admission routes1
Has abstractyes

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