Modulation of the attentional blink by differential resource allocation.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When one masked target (T2) follows another (T1) in close temporal proximity, identification accuracy of the second target is reduced for a period referred to as the attentional blink. Analysis of the attentional blink literature suggests that increasing the difficulty of T1 processing increases the magnitude of the blink. In a previous study that eliminated several untoward features of the typical attentional blink design (e.g., task switching, location switching, and stream contribution), we found no effect on blink magnitude when three levels of T1 difficulty (manipulated in a data-limited manner) were randomly intermixed. Here, when we repeated the previous study using a blocked manipulation of T1 difficulty, which is characteristic of the literature, a significant positive relation between T1 difficulty and blink magnitude was found. Resource allocation put in place to encode T1 in advance of a dual-target trial thus seems to be the critical factor in mediating this relation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it