Inhibition of Return and Repetition Priming Effects in Localization and Discrimination Tasks.
Bibliographic record
Abstract
Inhibition of return (IOR) refers to slower responding to a stimulus that is presented at the same, rather than a different location as a preceding, spatially nonpredictive, stimulus. Repetition priming refers to speeded responding to a stimulus that duplicates the visual characteristics of a stimulus that precedes it. IOR and repetition priming effects interact in nonspatial discrimination tasks but not in localization tasks; three experiments examined whether this is due to processing differences or due to response differences between tasks. Two stimuli, S1 and S2, occurred on each trial. In Experiment 1, S1 and S2 were both peripheral arrows; in Experiment 2, S1 was a central arrow and S2 was a peripheral nondirectional rectangle; in Experiment 3, S1 was a peripheral nondirectional rectangle and S2 was a peripheral arrow. S1 never required a response; S2 required a localization or a discrimination response. Despite evidence that form information was likely extracted from the arrow stimuli, the localization task revealed no repetition priming: IOR occurred regardless of shared visual identity of the S1 and S2 arrows. The discrimination task revealed IOR only when the visual identity changed from S1 to S2; otherwise, facilitation occurred. These results suggest that IOR is masked by repetition priming only when the response depends on the explicit processing of form information; repetition priming does not occur when such information is extracted automatically but is task (and response) irrelevant.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".