Temporal Expectancy, Framing Effects, and the Modulation of Inhibition of Return
Bibliographic record
Abstract
Recent studies eliminated volitional temporal preparation in single location inhibition of return (IOR) studies, but reported conflicting results regarding the contribution of volitional attention on single location IOR in detection tasks. We used a multiple location IOR paradigm to examine the contribution of voluntary attention to the typically observed finding of the greatest magnitude of IOR at the most recently cued location following multiple cues. A non-ageing foreperiod was used to eliminate volitional temporal preparation. When subjects were informed of the probability of a trial type (50% after cue 1, 25% after cue 2, and 12.5% after cue 3), typical results were observed with IOR largest at the most recently cued location and smaller for less recently cued locations on 3-cue trials. However, when subjects were informed of the frequency of a trial type (i.e., on 50 of the 100 trials, the target will appear after cue 1 etc), the results showed that IOR was equivalent at all cued locations, suggesting that IOR is fundamentally a reflexive event that can be modulated by volitional attention. (Manuscript in preparation)
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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 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".