Varied-mapping conjunction search: Evidence for rule-based learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Five experiments were carried out to examine whether top-down processes can aid search, even when targets and distractors are variably mapped. Experiments 1a and 1b determined that effortless VM search can be obtained in Contrast Polarity X Orientation and Color X Orientation conjunction search when one feature dimension remains consistently mapped across blocks. Experiment 2 showed that efficient VM search is possible when both dimensions are variably mapped. In Experiment 3, efficient VM search was found when target-distractor reversals occurred on a trial-wise basis. Experiments 4 and 5 found that VM search deteriorates when target identity is not known prior to display onset. These studies demonstrate the role of top-down mechanisms in the development of efficient VM search and present several challenges to strength-theoretic views on the mechanisms underlying automaticity.
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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 | 0.000 | 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) | 0.002 | 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 it