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Record W2119914203 · doi:10.1037/0096-1523.29.5.846

Explicit mechanisms do not account for implicit localization and identification of change: An empirical reply to Mitroff et al. (2002).

2003· article· en· W2119914203 on OpenAlexaff
Diego Fernandez‐Duque, Ian M. Thornton

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsWomen's College HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsIdentification (biology)Representation (politics)Cognitive psychologyAffect (linguistics)PsychologyPoint (geometry)Social psychologyEmpirical researchComputer scienceEpistemologyMathematicsCommunicationPolitical sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

Several recent findings support the notion that changes in the environment can be implicitly represented by the visual system. S. R. Mitroff, D. J. Simons, and S. L. Franconeri (see record 2002-15293-003) challenged this view and proposed alternative interpretations based on explicit strategies. Across 4 experiments, the current study finds no empirical support for such alternative proposals. Experiment 1 shows that subjects do not rely on unchanged items when locating an unaware change. Experiments 2 and 3 show that unaware changes affect performance even when they occur at an unpredictable location. Experiment 4 shows that the unaware congruency effect does not depend simply on the pattern of the final display. The authors point to converging evidence from other methodologies and highlight several weaknesses in Mitroff et al's theoretical arguments. It is concluded here that implicit representation of change provides the most parsimonious explanation for both past and present findings. ((c) 2003 APA, all rights reserved)

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)0.000
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 score0.082
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.250
GPT teacher head0.484
Teacher spread0.234 · 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

Citations66
Published2003
Admission routes1
Has abstractyes

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