Recollective performance advantages for implicit memory tasks
Bibliographic record
Abstract
A commonly held assumption is that processes underlying explicit and implicit memory are distinct. Recent evidence, however, suggests that they may interact more than previously believed. Using the remember-know procedure the current study examines the relation between recollection, a process thought to be exclusive to explicit memory, and performance on two implicit memory tasks, lexical decision and word stem completion. We found that, for both implicit tasks, words that were recollected were associated with greater priming effects than were words given a subsequent familiarity rating or words that had been studied but were not recognised (misses). Broadly, our results suggest that non-voluntary processes underlying explicit memory also benefit priming, a measure of implicit memory. More specifically, given that this benefit was due to a particular aspect of explicit memory (recollection), these results are consistent with some strength models of memory and with Moscovitch's (2008) proposal that recollection is a two-stage process, one rapid and unconscious and the other more effortful and conscious.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".