The Attentional Blink is Immune to Masking-Induced Data Limits
Bibliographic record
Abstract
The attentional blink is the robust finding that processing a masked item (T1) hinders the subsequent identification of a backwards masked second item (T2), which follows soon after the first one. There has been some debate about the theoretically important relation between the difficulty of T1 processing and the ensuing blink. In Experiment 1 we manipulated the difficulty of T1 in such a way as to affect the quality of data without altering the amount of resources allocated to its identification. We found no relation between the accuracy of T1 identification and the blink. In Experiment 2, the same difficulty manipulation was applied to T2, and we observed an additive pattern with the blink. Together, this pattern of results indicates that a data-limited difficulty manipulation does not affect the blink, whether applied to T1 or T2. In Experiment 3 we used an individual differences methodology to show that performance in the traditional "stream"-like presentation (rapid serial visual presentation) was highly correlated with performance in our modified "target mask, target mask" paradigm, thus allowing for comparisons beyond the present methodology to much of the previous literature that has used the stream paradigm.
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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 | 0.002 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".