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Semantic feature production norms for a large set of living and nonliving things

2005· article· en· 1,102 citations· W2078894097 on OpenAlex· 10.3758/bf03192726

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.177
GPT teacher head0.554
Teacher spread
0.377 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

No abstract. This is not a gap in this database — OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

The record

Venue
Behavior Research Methods
Topic
Child and Animal Learning Development
Field
Psychology
Canadian institutions
The Scarborough HospitalUniversity of TorontoWestern University
Funders
National Institute on Deafness and Other Communication DisordersNational Institute of Mental HealthU.S. Public Health ServiceNational Institutes of Health
Keywords
CategorizationSet (abstract data type)Feature (linguistics)Computer scienceCognitive psychologySemantic memorySemantic featurePsychologyNeuropsychologySemantics (computer science)Cognitive scienceNatural language processingArtificial intelligenceCognitionLinguistics
Has abstract in OpenAlex
no