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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

VenueAnnual Review of Psychology · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsEthologyCognitionCognitive sciencePsychologyComparative psychologyNatural selectionAnimal cognitionSocial cognitionEvolutionary psychologyNeuroanatomySelection (genetic algorithm)Brain sizeCognitive psychologyEcologyNeuroscienceBiologySocial psychologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Neuroecology is the study of adaptive variation in cognition and the brain. The origin of neuroecology dates from the 1980s, when researchers in behavioral ecology began to apply the methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. The comparative approach, however, is much older. It was a mainstay of ethology, it has been part of the study of neuroanatomy since the seventeenth century, and it was used by Darwin to marshal evidence for the theory of natural selection. Neuroecology examines the relations between ecological selection pressures and species or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural selection acts on cognition and its neural mechanisms. This chapter describes the general approach of neuroecology, phylogenetic comparative methods used in the field, and new findings on the cognitive mechanisms and brain structures involved in mating systems, social organization, communication, and foraging. The contribution of neuroecology to psychology and the neurosciences is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.068
GPT teacher head0.480
Teacher spread0.413 · 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