Searching for IOR: Review and Results
Bibliographic record
Abstract
Inhibition of return (IOR) has been proposed as an attentional mechanism which facilitates visual search by inhibiting reorienting to previously attended spatial locations. IOR is typically measured following the removal of attention from a spatial location. Early facilitation of responses to this location at early stimulus-onset asynchrony (SOA of ∼100 – 300ms) is replaced with a later and long-lasting inhibition (SOA of ∼300 – 3000ms). This inhibition has been proposed to be used by the oculomotor system to tag previously fixated locations in visual search to favour new locations over old (yet still salient) locations. Indeed, slower responses to probes presented in recently fixated locations has since been demonstrated in a variety of visual search tasks, and this form of IOR has been related to the reduced likelihood of refixating the previous or penultimate search location during natural search (MacInnes and Klein, 2003). However, recent research has challenged this interpretation by suggesting that saccadic momentum facilitates forward saccades as opposed to IOR suppressing return saccades. For instance, Smith and Henderson (2010) replicated Klein and MacInnes (1999) by finding IOR in a Where's Waldo © search task, but they reanalyzed the probability distribution of saccades to provide evidence for a saccadic momentum account. This talk will provide a review of recent research outlining the evidence for IOR and saccadic momentum in natural search patterns and present new data on the distribution of saccades in complex search tasks. [Supported by BBSRC]
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".