A Review of the Association Between Environmental Harshness, Neurogenesis and Caching Behaviour
Bibliographic record
Abstract
Memory is one of the most crucial cognitive functions in many organisms. It is highly implicated in everyday functioning and is an essential component for survival. Past research has revealed that spatial memory facilitates bird caching behaviours such as remembering the exact locations of their hidden food. However, there are many factors that alter the demands on memory and consequently impact the function of caching. Specifically, neurogenesis, the process of forming new neurons, has been shown to affect this behaviour. Likewise, environmental variables and selective pressures (i.e., severity of the environment) can also influence caching in birds. In this review, we present evidence for a link between environmental harshness, hippocampal neurogenesis, and caching behaviour in chickadees, with specific focus on work by Chancellor et al. [6]. Neurogenesis in chickadees may be a mechanism subject to selective pressures, in which chickadees from harsher environments have increased neurogenesis rates and consequently enhanced caching ability. However, there remain gaps in the understanding of how exactly hippocampal neurogenesis, environmental harshness, and caching behaviour interact, and future studies are needed to further explore this interaction and its implications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".