Bibliographic record
Abstract
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.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".