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Record W2015174774 · doi:10.1037/0278-7393.27.1.236

Relation and lexical priming during the interpretation of noun–noun combinations.

2001· article· en· W2015174774 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2001
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsWestern University
Fundersnot available
KeywordsNounPriming (agriculture)LinguisticsHead (geology)Interpretation (philosophy)Schema (genetic algorithms)Lexical decision taskNatural language processingPsychologyArtificial intelligenceMathematicsComputer sciencePhilosophyCognitionBiologyBotanyInformation retrieval

Abstract

fetched live from OpenAlex

This research indicates that recent exposure to a similar combination (e.g., oil moisturizer or surgery treatment) influences the processing of a subsequent combination (e.g., oil treatment) by increasing the availability of the lexical entries for the modifier and head noun, and by altering the availability of the relation used to link the two nouns. The amount of lexical and relational priming obtained depends on whether the modifier or head noun is in common between the prime and target. The head noun prime yields more lexical priming than does the modifier prime and this finding suggests that the head noun is more strongly activated than the modifier. In contrast, relation priming is obtained only from the modifier prime and this finding is consistent with the CARIN theory (C. L. Gagné & E. J. Shoben, 1997) but inconsistent with schema-based theories of conceptual combination (e.g., G. L. Murphy, 1988; E. J. Wisniewski, 1996).

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.217

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)0.0000.000

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 head0.026
GPT teacher head0.331
Teacher spread0.306 · 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