Individual Differences Within and Across Attentional Blink Tasks Revisited
Bibliographic record
Abstract
When the second of two targets (T2) is presented in close temporal proximity (within 200-500 ms) to the first (T1), accuracy for reporting T2 is reduced relative to when the targets are separated by longer durations--the attentional blink (AB). Two recent studies have shown that individual differences in the magnitude of the AB are stable both within a single testing session and over time. While one study found a large positive correlation between AB magnitude when there was an attentional set/task switch between T1 and T2 and when there was not, the other study found no relationship between switch and no-switch paradigms. The current study was conducted to clarify this discrepancy by examining the reliability of, and relationships among, individual differences in AB performance on 5 different versions of the standard dual-target RSVP paradigm (three of which involved an attentional set/task switch between T1 and T2, and two of which did not). Participants completed all 5 paradigms, and then returned 7-10 days later to again complete the same paradigms. All 5 versions were reliable both within, and across, testing sessions, demonstrating again that individual differences in AB performance are stable over time. In addition, all 5 AB versions were significantly intercorrelated, although the strength of the relationship differed depending on the extent to which the T1 and T2 attentional sets/tasks overlapped. These findings provide evidence that multiple distinct dual-target RSVP tasks do share underlying variability, providing support for the use of different versions of the paradigm in the literature. Meeting abstract presented at VSS 2013
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".