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Record W2078609322 · doi:10.1002/dev.21017

Malleability in the development of spatial reorientation

2012· article· en· W2078609322 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDevelopmental Psychobiology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsMalleabilityFeature (linguistics)PsychologyPerspective (graphical)Contrast (vision)Coding (social sciences)Cognitive psychologyDevelopmental psychologyArtificial intelligenceComputer scienceMathematicsLinguisticsStatistics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.156
GPT teacher head0.364
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it