Malleability in the development of spatial reorientation
Bibliographic record
Abstract
After becoming disoriented, organisms must re-establish their position in space. The core knowledge position argues that reorientation relies only on extended 3D surfaces, and that this sensitivity operates automatically and is innately present. In contrast, the adaptive combination perspective argues that reorientation is experience-expectant and malleable, and depends on both extended 3D surfaces and 2D feature cues. We test these divergent views by comparing young (Experiment 1) and mature (Experiment 2) C57BL/6 mice (Mus musculus) that have been housed in circular or rectangular environments. Malleability of feature cues was found for young mice. Malleability of incidental geometry coding was found for both age groups. The relative dependence on geometric and feature cues changed with age. Young mice weighted the feature cue more heavily than adult mice. In summary, as predicted by the adaptive combination approach, rearing environments influenced the relative use of feature and geometric cues in a reorientation task.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".