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Record W2050771282 · doi:10.3389/fnhum.2012.00113

The influence of print exposure on the body-object interaction effect in visual word recognition

2012· article· en· W2050771282 on OpenAlexafffund
Dana Hansen, Paul D. Siakaluk, Penny M. Pexman

Bibliographic record

VenueFrontiers in Human Neuroscience · 2012
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of CalgaryUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHumWord (group theory)Object (grammar)PsychologyCommunicationComputer scienceSpeech recognitionLinguisticsArtificial intelligenceArt

Abstract

fetched live from OpenAlex

We examined the influence of print exposure on the body-object interaction (BOI) effect in visual word recognition. High print exposure readers and low print exposure readers either made semantic categorizations ("Is the word easily imageable?"; Experiment 1) or phonological lexical decisions ("Does the item sound like a real English word?"; Experiment 2). The results from Experiment 1 showed that there was a larger BOI effect for the low print exposure readers than for the high print exposure readers in semantic categorization, though an effect was observed for both print exposure groups. However, the results from Experiment 2 showed that the BOI effect was observed only for the high print exposure readers in phonological lexical decision. The results of the present study suggest that print exposure does influence the BOI effect, and that this influence varies as a function of task demands.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.034
GPT teacher head0.330
Teacher spread0.296 · 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

Citations18
Published2012
Admission routes2
Has abstractyes

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