Relation availability was not confounded with familiarity or plausibility in Gagné and Shoben (1997): Comment on Wisniewski and Murphy (2005).
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".