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Record W2320067345 · doi:10.5406/amerjpsyc.124.2.0163

New Variations of Intrahemispheric and Interhemispheric Processing Indexed by the Dimond Paradigm

2011· article· en· W2320067345 on OpenAlexaff
Claude M. J. Braun, André Achim, Geoffrey Gauvin, Samuel Desjardins, Carl Roberge, Sabrina Suffren

Bibliographic record

VenueThe American Journal of Psychology · 2011
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyTask (project management)PerceptionCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

We report 2 experiments designed to demonstrate that unilateral tachistoscopic stimulation would yield a response time (RT) advantage over bilateral stimulation in a simple experiment, whereas the opposite pattern would occur in a complex version of the same task, as predicted by the intrahemispheric resource limitation model of Banich and colleagues. Experiment 1 was a go/no-go task in which participants had to press a key when two shapes (circles or squares) were identical on the computer screen. A unilateral field advantage was obtained that was accentuated in several task conditions that yielded overall longer RTs, mostly in the bilateral condition. Experiment 2 was similar but required a more complex judgment: The go trials were to 2 stimuli identical on 1 dimension (shape or color) but not both or neither. The RTs were significantly and substantially longer than in Experiment 1 and exhibited a nonsignificant bilateral field advantage, which differed significantly from the unilateral field advantage obtained in Experiment 1. These results support the intrahemispheric resource limitation model of Banich and colleagues. However, several within-experiment effects are in direct opposition to this model and are best explained as limitations of commissural relay of perceptual information.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.281

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 studies0.0000.001
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 head0.057
GPT teacher head0.341
Teacher spread0.284 · 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 designBench or experimental
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

Citations8
Published2011
Admission routes1
Has abstractyes

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