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Record W1009596468

Assimilation between two neighboring time intervals marked with tactile stimuli

2012· article· en· W1009596468 on OpenAlexaff
Emi Hasuo, Tsuyoshi Kuroda, Simon Grondin

Bibliographic record

VenueProceedings of Fechner Day · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDuration (music)AudiologyIllusionTime perceptionPerceptionInterval (graph theory)PsychologyPsychophysicsMathematicsCognitive psychologyMedicinePhysicsAcousticsNeuroscienceCombinatorics
DOInot available

Abstract

fetched live from OpenAlex

The aim of this study was to examine whether and how the perception of an empty time interval marked by two brief tactile stimuli, S, is influenced by the duration of the preceding time interval, P. In each trial, three electric pulses, each lasting 20 ms, were successively delivered to the right hand of participants, the first two pulses marking P and the last two marking S. S was fixed at 240 ms while P was 160, 240, or 320 ms. In addition, there was a control condition where S was presented in isolation (without P). Perceived duration of S was estimated with the method of constant stimuli. Results showed that participants underestimated S when P was 160 ms. This underestimation appeared as a kind of perceptual assimilation between P and S, but indeed S was not overestimated when it was preceded by a longer interval (P = 320 ms). The underestimation was rather regarded as the time-shrinking illusion which had been tested with visual and auditory stimuli.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.300
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

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