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Record W2065143701 · doi:10.1075/ml.4.1.03gag

Does s <i>now man</i> prime <i>plastic snow</i>?

2009· article· en· W2065143701 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

VenueThe Mental Lexicon · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRelation (database)Prime (order theory)Priming (agriculture)NounInformation processingComputer scienceArtificial intelligenceNatural language processingLinguisticsMathematicsPsychologyCognitive psychologyData miningCombinatoricsPhilosophyBiology

Abstract

fetched live from OpenAlex

Three experiments were conducted to determine the extent to which relational and morphosyntactic information influence the processing of modifier-noun phrases. Processing of the target was faster when the shared constituent was in the same position in both the prime and the target, regardless of whether the relation was the same or different. In contrast, relation priming was contingent on the morphosyntactic role of the shared constituent; repeating the relation with the constituent in a different morphosyntactic role did not speed processing of the target (Experiments 1–3) whereas repeating the relation with the constituent in the same role did speed processing (Experiments 3). These results suggest that conceptual information is accessed in light of the constituent’s particular morphosyntactic role.

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 score0.010
Threshold uncertainty score0.570

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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