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Record W2020103944 · doi:10.1177/0146167201272005

The Sounds and Sights of Intelligence: A Lens Model Channel Analysis

2001· article· en· W2020103944 on OpenAlexaff
D’Arcy J. Reynolds, Robert Gifford

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2001
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychologySensory cueContext (archaeology)Cognitive psychologySightVisual perceptionPerceptionNeuroscience

Abstract

fetched live from OpenAlex

The links between 13 auditory and visual behavioral cues, measured intelligence, and observer judgments of intelligence in a zero-acquaintance context were examined in a lens model study. Auditory-plus-visual, auditory-only, and visual-only information conditions, in addition to a transcript-only control condition, were employed to determine whether auditory or visual cues encode measured intelligence more strongly and which are used more in judgments of intelligence. Five cues (of both types) accounted for nearly half the variance in measured intelligence, but it was much more strongly associated with auditory than visual cues. Observers’ judgments of intelligence were also much more strongly related to auditory than visual cues. Visual cues may even depress accuracy; accuracy was higher in an auditory-only condition than in an auditory-plus-visual condition.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.669

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 studies0.0010.002
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 head0.221
GPT teacher head0.408
Teacher spread0.187 · 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 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

Citations85
Published2001
Admission routes1
Has abstractyes

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