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Record W2061552568 · doi:10.1037/0278-7393.32.6.1431

Relation availability was not confounded with familiarity or plausibility in Gagné and Shoben (1997): Comment on Wisniewski and Murphy (2005).

2006· letter· en· W2061552568 on OpenAlexaff
Christina L. Gagné, Thomas L. Spalding

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2006
Typeletter
Languageen
FieldComputer Science
TopicAdvanced Text Analysis Techniques
Canadian institutionsUniversity of Alberta
FundersNational Institute of Mental Health
KeywordsRelation (database)PhrasePsychologyArtificial intelligenceComputer scienceData mining

Abstract

fetched live from OpenAlex

C. L. Gagné and E. Shoben (1997) proposed that the conceptual system contains information about how concepts are used to modify other concepts and that this relational information influences the ease with which concepts combine. Recently, E. J. Wisniewski and G. L. Murphy suggested that C. L. Gagné and E. Shoben's measure of relation availability was confounded with familiarity and plausibility and that the participants could simply retrieve the stored meanings of the phrases because the phrases were not novel. In this article, the authors demonstrate that E. J. Wisniewski and G. L. Murphy's plausibility and familiarity judgments are dependent variables that (a) are themselves responsive to changes in relation availability, (b) modifier relation availability predicts response time even when the influence of phrase familiarity and plausibility is controlled, and (c) the materials consisted of mainly novel phrases.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.004
Open science0.0040.002
Research integrity0.0140.010
Insufficient payload (model declined to judge)0.0090.006

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 head0.033
GPT teacher head0.326
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations18
Published2006
Admission routes1
Has abstractyes

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