Bibliographic record
Abstract
There is growing evidence that attention is important for many aspects of perception.Recognition of a stimulus can be strongly degraded if a second stimulus is presented less than 150 ms later ("visual masking effect").Masking strength is influenced by the physical characteristics of the stimuli and the effect is even stronger if attentional processes are focused on another object ("Attentional blink, AB").The first part of our project examined the reasons for the increased masking effect during inattention.Our resuits suggest that visual masking is stronger when the mask is a new visual object in the visual scene, but is flot modulated when target and mask are presented simultaneousÏy.In a second part, we measured cerebral activity using functional magnetic resonance imaging during visual masking.We found that activity in occipito-temporal cortex was inftuenced by sequential rnasks more than by simultaneous masks.Recognition performance correlated with activity in temporo-parietal areas.Our results suggest that the effect of inattention on visual masking is linked to the detection and the consolidation of new objects in the visual scene, and that this effect involves the occipito-temporal cortex.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".