The effects of face inversion on the perception of long-range and local spatial relations in eye and mouth configuration.
Bibliographic record
Abstract
A recent study hypothesized a configurational anisotropy in the face inversion effect, with vertical relations more difficult to process. However, another difference in the stimuli of that report was that the vertical but not horizontal shifts lacked local spatial references. Difficulty processing long-range spatial relations might also be predicted from a relevance-interaction explanation, which proposes that in inverted faces, spatial relations are processed efficiently only within high-relevance local regions. The authors performed 2 experiments to distinguish between these hypotheses. Experiment 1 showed that the inversion effect for vertical shifts of the eyes alone was more similar to that for horizontal eye shifts than for vertical shifts of the eyes and eyebrows. In Experiment 2, focused attention reduced the inversion effect for vertical mouth position more than that for vertical shifts of the eyes and brows. The authors concluded that face inversion impairs the perception of both local spatial relations in low-relevance regions and long-range spatial relations extending across multiple facial regions, consistent with a loss of efficient whole-face processing of the spatial relations between features.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".