Proactive control: Endogenous cueing effects in a two-target attentional blink task
Bibliographic record
Abstract
This study examined proactive control in a two-target task using an endogenous cueing method. Participants identified two target words (T1 then T2) presented in rapid succession. T1 was presented alone or interleaved with a distractor word. In Experiment 1, informative pre-cues that signalled T1 selection difficulty were randomly intermixed with uninformative pre-cues. The results revealed a cueing effect for both T1 and T2, with better performance for informative cues than for uninformative cues. In Experiment 2, informative and uninformative cues were mixed for one group, and blocked for another group. In the mixed cue group, we again found a T2 cueing effect. In the blocked cue group, a cueing effect was observed for both T1 and T2, with the T2 cueing effect restricted to the shortest T1-T2 SOA. The results demonstrate that pre-cues of attentional conflictcan modulate performance in a two-target task used to measure the attentional blink.
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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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".