Attentional requirements in visual detection and identification: Evidence from the attentional blink.
Bibliographic record
Abstract
Perception of the 2nd of 2 targets (T1 and T2) is impaired if the lag between them is short (0-500 ms). The authors used this attentional blink (AB) to index attentional requirements in detection and identification tasks, with or without backward masking of T2, in 2 stimulus domains (line orientation, coherent motion). With masking, the AB occurred because T2 was masked during the attentional dwell time created by T1 processing (Experiments 1, 2, and 3). Without masking, an AB occurred only in identification because during the attentional dwell time, T2 decayed to a level that could support simple detection but not complex identification. However, an AB occurred also in detection if T2 was sufficiently degraded (Experiment 4). The authors drew 2 major conclusions: (a) Attention is required in both identification and detection, and (b) 2 factors contribute to the AB, masking of T2 while attention is focused on T1 and decay of the T2 trace while unattended.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".