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Record W4417423506 · doi:10.3390/ani15243628

The Map’s Design: Evolution’s Impact on Navigation and Spatial Cognition

2025· article· en· W4417423506 on OpenAlexafffund
Isabella S. Olynik-McLaughlin, Diano F. Marrone

Bibliographic record

VenueAnimals · 2025
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCognitionSpatial cognitionPerceptionAnimal cognitionFunction (biology)Focus (optics)Cognitive mapComparative cognition

Abstract

fetched live from OpenAlex

Spatial cognition is fundamental to an animal's ability to move through and interact with its environment. Thus, understanding the physiological basis for this cognitive function and how it varies across taxa is fundamental to understanding how ecology alters brain architecture and function. Although elements of spatial cognition can be found across the animal kingdom, here we concentrate specifically on cognitive maps and their physiological basis. This will begin with a focus on the rodent model, which is the source of the vast majority of data on the neural basis of cognitive maps. This serves as a foundation for comparative analysis of other taxa to demonstrate that, although this line of inquiry is relatively new and small, important variations have been observed, tied largely to changes in both perception and ambulation, that may fundamentally alter how spatial cognition is implemented. This latter analysis emphasizes birds, as recent data in this order provide fundamental insights into how the selective pressures that drive changes in peripheral physiology also drive commensurate neuronal changes in spatial cognition.

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.

How this classification was reachedexpand

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)0.000
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 score0.033
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.073
GPT teacher head0.344
Teacher spread0.271 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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