Event-related potential evidence for a dual-locus model of global/local processing
Bibliographic record
Abstract
We investigated the perceptual time course of global/local processing using event-related potentials (ERPs). Participants discriminated the global or local level of hierarchical letters of different sizes and densities. Participants were faster to discriminate the local level of large/sparse letters and the global level of small/dense letters. This was mirrored in early ERP components: The N1/N2 had smaller peak amplitudes when participants made discriminations at the level that took precedence. Only global discriminations for large/sparse letters led to amplitude enhancement of the later P3 component, suggesting that additional attention-demanding processes are involved in discriminating the global level of these stimuli. Our findings suggest a dual-locus time course for global/local processing: (a) Level precedence occurs early in visual processing; (b) extra processing is required at a later stage, but only for global discriminations of large, sparse, stimuli, which may require additional attentional resources for active grouping.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".