Bibliographic record
Abstract
In the 1980s and 1990s, there was a major theoretical debate in the memory domain regarding the multiple memory systems and processing modes frameworks. The components of processing framework argued for a middle ground: Instead of neatly divided memory systems or processing modes, this framework proposed the existence of numerous processing components that are recruited in different combinations by memory tasks and yield complex patterns of associations and dissociations. Because behavioral evidence was not sufficient to decide among these three frameworks, the debate was largely abandoned. However, functional neuroimaging evidence accumulated during the last two decades resolves the stalemate, because this evidence is more consistent with the components framework than with the other two frameworks. For example, functional neuroimaging evidence shows that brain regions attributed to one memory system can contribute to tasks associated with other memory systems and that brain regions attributed to the same processing mode (perceptual or conceptual) can be dissociated from each other. Functional neuroimaging evidence suggests that memory processes are supported by transient interactions between a few regions called process-specific alliances. These conceptual developments are an example of how functional neuroimaging can contribute to theoretical debates in cognitive psychology.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.007 | 0.016 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".