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Record W2041767045 · doi:10.1371/journal.pone.0042963

Negative Priming in a Joint Selection Task

2012· article· en· W2041767045 on OpenAlexafffund
Timothy N. Welsh, Laura McDougall

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of CalgaryUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPriming (agriculture)Cognitive psychologyTask (project management)PsychologyCognitionSelection (genetic algorithm)Variety (cybernetics)Computer scienceSocial psychologyBiologyNeuroscienceArtificial intelligence

Abstract

fetched live from OpenAlex

Recent studies have suggested that the observation of another individual executing a movement activates representations of the observed movement in the observer. These representations are thought to be used by other systems to facilitate a variety of social cognitive processes, such as social searches. Previous research on social searches has primarily involved contexts where targets were presented in isolation. Typical environments, however, contain targets and non-targets and one must select the correct information for task completion. To gain insight into the processes underlying social searches, participants completed negative priming tasks alone and in pairs. Results indicated that there were no differences in the negative priming effects resulting from the participants observed or performed the preceding selection task. Further, the correlations between individual and joint negative priming suggest that similar processes were activated on these tasks. The findings support the co-representation hypothesis and provide insight into the processes underlying selection in individual and social settings.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.134
GPT teacher head0.299
Teacher spread0.165 · 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.

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

Citations5
Published2012
Admission routes2
Has abstractyes

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