Automatic versus volitional orienting and the production of the inhibition-of-return effect.
Bibliographic record
Abstract
A single, to-be-ignored peripheral flash (i.e., cue) reflexively attracts an orienting response (oculomotor/attention/head turn) that ultimately causes reaction time delays to target stimuli that later arise at this cued location, in relation to when the target appears at a new position (i.e., the inhibition-of-return [IOR] effect). The basic question posed here dealt with whether an IOR effect is also produced following volitional orienting. Results from paired cue-trial stimulations, one a distractor and one a target (nonsalient/salient) event, positioned more or less symmetrically on either side of fixation, supported the net vector model of IOR (R. Klein, J. Christie, & E. P. Morris, 2005). Automatic orienting did not yield an IOR effect at the stimulated positions. When the need to later report cue-trial target location was added, an IOR effect appeared at distractor-occupied, but not at target-occupied, locations. Seemingly, an IOR effect can follow volitional orienting. In this instance, the IOR process seems capable of undergoing modulation; however, such modulation was not evident following automatic orienting.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".