Perception of temporal order is impaired during the time course of the attentional blink.
Bibliographic record
Abstract
Identification accuracy for the second of two target (T2) is impaired when presented shortly after the first (T1). Does this attentional blink (AB) also impair the perception of the order of presentation? In four experiments, three letter targets (T1, T2, T3) were inserted in a stream of digit distractors displayed in rapid serial visual presentation (RSVP), with T3 always presented directly after T2. The T1-T2 lag was varied to assess the perception of T2-T3 temporal order throughout the period of the AB. Factorial manipulation of the presence or absence of distractors before T1 and between T1 and T2 had similar effects on accuracy and on perception of temporal order. It is important to note that perception of temporal order suffered even when accuracy was unimpaired. This pattern of results is consistent with prior-entry theories of the perception of temporal order but not with episodic-integration theories. Simulations based on the Episodic Simultaneous Type, Serial Token (eSTST) model (Wyble, Bowman, & Nieuwenstein, 2009) provided excellent fits to the data except for the condition in which no distractors were presented in the RSVP stream.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".