Lag-1 sparing in accuracy and reaction time: The importance of masking
Bibliographic record
Abstract
Perception of the second of two rapidly sequential targets (T1, T2) is impaired when presented soon after the first (attentional blink; AB). In an exception, known as Lag-1 sparing, T2 performance is relatively unimpaired when it comes directly after T1. Lag-1 sparing is typically found when the dependent measure is T2 accuracy. In contrast, Lag-1 deficit is observed when the dependent measure is reaction time (RT; Lagroix, Di Lollo, & Spalek, 2015). A notable methodological difference between experiments that measured accuracy and those that measured RT was that T2 was followed by a mask in the former but not in the latter. In the present work, we demonstrate that Lag-1 sparing can be obtained with RT as the dependent measure, but only if T2 is followed by a mask. In contrast, when the dependent measure is T2 accuracy, Lag-1 sparing is in evidence whether or not T2 is masked. These results have implications beyond the phenomenon of Lag-1 sparing. They suggest that accuracy and RT are not always equivalent measures, and suggest that the AB may arise from postponement of T2 processing at more than one level within the system. This is inconsistent with extant theories in which the AB is said to occur at a single stage of processing. Meeting abstract presented at VSS 2016
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".