Bibliographic record
Abstract
A growing body of research has shown that spatial attention alters stimulus appearance on a number of dimensions including contrast (Carrasco, Ling, & Read, 2004), spatial resolution (Gobell & Carrasco, 2005), and size (Anton-Erxleben, Henrich, & Treue, 2007). Here we explored whether feature-based attention would also influence perceived spatial resolution, and whether its influence would mirror that of spatial attention. Each trial began with a brief presentation of a colored cue in order to direct feature-based attention to that cue's color. Following the cue presentation, a stimulus display was presented consisting of two differently-colored Landolt squares-one of which matched the cue color on 66% of the trials. Participants performed a two-alternative forced-choice discrimination task requiring them to provide a response indicating which of the two Landolt squares possessed the larger gap. Our results suggested that the effect of feature-based attention on perceptual experience may be different than that of spatial attention.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".