Evidence of episodic storage processing in a visuo-spatial task
Bibliographic record
Abstract
The main objective in this investigation was to determine whether processed information in visuo-spatial tasks is stored episodically, relying on the view that a distinguishing feature of episodic storage is that the episode includes both relevant (target) and irrelevant (distractor) display information. Accordingly, one untested prediction of episodic storage is that if either a target or a distractor event whose identity matches that of an earlier presentation is presented alone, it should nonetheless result in the concurrent retrieval of both events (i.e., 'indirect retrieval' prediction). Two spatial negative priming (SNP) tasks using sequential prime-probe trial pairs, distinguished with respect to the likelihood of a probe trial distractor appearing (i.e., .75[Exp. 1A], .25[Exp. 1B]) were used, where evidence of 'error protection' replaced the spatial negative priming effect as the index of prime distractor representation retrieval. The results revealed that certain target-only probe trial configurations that successfully retrieved prime target representations (i.e., direct retrieval), also showed evidence of the concomitant retrieval of stored distractor representations (i.e., indirect retrieval). This supported the episodic storage of information in visuo-spatial tasks, converging with (Neill, Valdes, Terry, & Gorfein, 1992). On lesser matters, direct retrieval of distractor objects was demonstrated and feature binding was not observed. Key Words: Episodic, Error Protection, Location TasksAcknowledgments: This work was supported by a grant from the Natural Sciences and Engineering Research Council of Canada to the second author.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".