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Record W2048772980 · doi:10.1080/13576500442000283

Constant and variable aspects of the dichotic listening right-ear advantage: A comparison of standard and signal detection tasks

2005· article· en· W2048772980 on OpenAlexaff
Merrill Hiscock, Roxanne Inch, Charisse Ewing

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2005
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDichotic listeningAsymmetryAudiologyPsychologyDetection theoryTask (project management)Two-alternative forced choicePerceptionContrast (vision)Cognitive psychologyActive listeningLateralitySpeech recognitionTest (biology)Developmental psychologyComputer scienceCommunicationArtificial intelligenceNeuroscienceMedicineTelecommunicationsDetector

Abstract

fetched live from OpenAlex

The study was designed to disentangle perceptual and attentional components of the dichotic listening right-ear advantage (REA). A total of 120 normal adults (108 right-handers and 12 left-handers) were administered the Halwes Fused Dichotic Words Test (FDWT) under standard conditions, which entail a forced-choice response format and no attention instructions. Two weeks later, the same stimuli were administered in a signal detection format with varied attention instructions (left, right, and equally divided). The standard task yielded the expected REA. The signal detection task yielded an REA for detection of targets that remained invariant across attention conditions. In contrast, ear asymmetry for localisation of targets varied with attention instructions. The REA on the standard task was correlated with the asymmetry of target detection (r = .57) on the signal detection task but not with the asymmetry of localisation or response bias. Ear asymmetry on the standard test seems to reflect an early stage of processing that is not altered by shifts of attention. Volitional shifts of attention influence the localisation of targets, but this component of signal processing is unrelated to the REA obtained on the standard test.

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)0.001
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 score0.010
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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

Citations13
Published2005
Admission routes1
Has abstractyes

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