Bibliographic record
Abstract
Merging evolutionary ecology and cognitive science, cognitive ecology investigates how animal interactions with natural habitats shape cognitive systems, and how constraints on nervous systems limit or bias animal behavior. Research in cognitive ecology has expanded rapidly in the past decade, and this second volume builds on the foundations laid out in the first, published in 1998. Cognitive Ecology II integrates numerous scientific disciplines to analyze the ecology and evolution of animal cognition. The contributors cover the mechanisms, ecology, and evolution of learning and memory, including detailed analyses of bee neurobiology, bird song, and spatial learning. They also explore decision making, with mechanistic analyses of reproductive behavior in voles, escape hatching by frog embryos, and predation in the auditory domain of bats and eared insects. Finally, they consider social cognition, focusing on alarm calls and the factors determining social learning strategies of corvids, fish, and mammals. With cognitive ecology ascending to its rightful place in behavioral and evolutionary research, this volume captures the promise that has been realized in the past decade and looks forward to new research prospects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.025 |
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".