Bibliographic record
Abstract
Much research has suggested that attention is biased away from previously attended locations-- a phenomenon termed inhibition of return (IOR). Traditionally, IOR studies use simple visual stimuli in detection tasks and employ a cue-target paradigm where a task-irrelevant cue is briefly presented followed by a target at either a cued location (same location as cue) or at an uncued location. Participants provide no response to the cue, but then produce a key press response upon target detection. When the stimulus onset asynchrony (SOA) is less than 300 ms, response to the target is facilitated by the cue; when the SOA is greater than 300 ms, response to the target is slowed at the cued location. The current study investigates different cue-target tasks and their effect on inhibition of return (IOR). We will conduct a between-subjects experiment with three conditions differing in response instruction. Target-only condition replicates the classic IOR study using a cue-target, detection task paradigm in which participants respond to the target but not the cue. Same-response condition requires participants to make identical responses to the cue and target. Different-response condition requires participants to provide a response to both the cue and the target, but the responses for the cue and target will differ. Together these studies help us understand the extent that IOR is caused by a motor response conflict as we compare the magnitude of IOR from the three testing conditions.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".