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Record W2164039012 · doi:10.1037/0096-1523.30.4.733

Decoupling Stimulus Duration From Brightness in Metacontrast Masking: Data and Models.

2004· article· en· W2164039012 on OpenAlexaff
Vincent Di Lollo, Adrian von Mühlenen, James T. Enns, Bruce Bridgeman

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2004
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBrightnessStimulus (psychology)LuminanceBackward maskingMonotonic functionMathematicsPsychologyPhysicsOpticsCognitive psychologyNeuroscienceMathematical analysisPerception

Abstract

fetched live from OpenAlex

A brief target that is visible when displayed alone can be rendered invisible by a trailing stimulus (metacontrast masking). It has been difficult to determine the temporal dynamics of masking to date because increments in stimulus duration have been invariably confounded with apparent brightness (Bloch's law). In the research reported here, stimulus luminance was adjusted to maintain constant brightness across all durations. Increasing target duration yielded classical U-shaped masking functions, whereas increasing mask duration yielded monotonic decreasing functions. These results are compared with predictions from 6 theoretical models, with the lateral inhibition model providing the best overall fit. It is tentatively suggested that different underlying mechanisms may mediate the U-shaped and monotonic functions obtained with increasing durations of target and mask, respectively.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.147
GPT teacher head0.411
Teacher spread0.264 · 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 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

Citations39
Published2004
Admission routes1
Has abstractyes

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