Masking of a first target in the attentional blink attenuates the <scp>P</scp>3 to the first target and delays the <scp>P</scp>3 to the second target
Bibliographic record
Abstract
The attentional blink (AB) refers to the decline in report accuracy of a second target (T2) when presented shortly after a first target (T1) in a rapid serial visual presentation (RSVP) of distractors. It is known that masking T1 increases the magnitude of the AB, and masking a single target (equivalent to T1) in a RSVP stream attenuates the P3 to the target in correct trials. The major purpose of the present study was to clarify how these two effects may be integrated. An intervening distractor was presented at lag 1 (T1+1), at lag 2 (T1+2), or at neither of these two lags (no distractor). T2 was always presented at lag 3, as the last item in the stream. The P3 to T1 was attenuated and the P3 to T2 delayed in the T1+1 condition compared to the two other distractor conditions. These results clearly show that masking T1 attenuates the P3 to T1 and delays the P3 to T2 in the AB. Implications for extant theories of the AB are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".