Distinct Mechanisms Account for the Linear non–Separability and Conjunction Effects in Visual Shape Encoding
Why this work is in the frame
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Bibliographic record
Abstract
In a series of visual search experiments involving simple 2D shapes, Arguin and Saumier (2000) showed that targets that were made of conjunctions of distractor features or that were a linear combination of distractor features were searched at significantly slower rates than single-feature linearly separable targets. The present study assessed whether these conjunction and linear nonseparability effects can be attributed to distinct mechanisms. Specifically, we studied the impact of target-distractor similarity on the search rates for single-feature, conjunction, and linearly nonseparable targets. The results replicate the conjunction and linear nonseparability effects obtained by Arguin and Saumier. They also show that the conjunction and linear separability effects are differently modulated by variations in target-distractor similarity. This dissociation demonstrates that both effects are based on distinct mechanisms. The possible nature of these mechanisms is discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it