Time course and robustness of ERP object and face differences
Bibliographic record
Abstract
Conflicting results have been reported about the earliest "true" ERP differences related to face processing, with the bulk of the literature focusing on the signal in the first 200 ms after stimulus onset. Part of the discrepancy might be explained by uncontrolled low-level differences between images used to assess the timing of face processing. In the present experiment, we used a set of faces, houses, and noise textures with identical amplitude spectra to equate energy in each spatial frequency band. The timing of face processing was evaluated using face-house and face-noise contrasts, as well as upright-inverted stimulus contrasts. ERP differences were evaluated systematically at all electrodes, across subjects, and in each subject individually, using trimmed means and bootstrap tests. Different strategies were employed to assess the robustness of ERP differential activities in individual subjects and group comparisons. We report results showing that the most conspicuous and reliable effects were systematically observed in the N170 latency range, starting at about 130-150 ms after stimulus onset.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".