On the relation between conceptual priming, neural priming, and novelty assessment
Bibliographic record
Abstract
A consistently reported finding in functional neuroimaging studies which compare processing of new information to processing of old information is a reduction in blood flow, and hence neural activity, associated with the old condition. This deactivation has been labeled neural priming. Some investigators have hypothesized that neural priming is the physiological mechanism underlying conceptual priming--a facilitation in the semantic processing of repeated information. Others, however, have hypothesized that neural priming reflects novelty assessment--a mechanism which minimizes the probability that redundant information will be stored in long-term memory. In this paper, the conceptual priming and novelty assessment hypotheses are compared and contrasted in order to ask, and tentatively answer, the question: Are conceptual priming and novelty assessment cognitively and neurophysiologically distinct? Based on a review of the literature, it is suggested that whereas novelty assessment and conceptual priming are distinct cognitive entities, they cannot be presently separated neurophysiologically. That is, some novelty assessment deactivations may in fact reflect priming, and some priming deactivations may in fact reflect novelty assessment.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".