Does brain size of Asiatic toads (<i>Bufo gargarizans</i>) trade-off with other energetically expensive organs along altitudinal gradients?
Bibliographic record
Abstract
Brain size variation is often attributed to energetic trade-offs with other metabolically expensive tissues and organs, which is a prediction of the expensive brain hypothesis (EBH). Here we examine Asiatic toads (Bufo gargarizans) along altitudinal gradients and test size trade-offs between the brain and four visceral organs (heart, liver, alimentary tract, and kidney) with altitude. Body size and scaled mass index (a proxy for total energy intake) decline with altitude, implying stronger energetic constraints at high altitudes. Relative brain size decreases along altitudinal gradients, while visceral organs mostly increase in relative sizes. Using structural equation modeling, a significant negative relationship between brain size and a latent variable "budget," which represents the energy allocation to the four visceral organs, is detected among high-altitudinal toads. Heart appears to have the largest and most consistent response to changes in energy allocation. No such relationships are observed among toads at middle- and low-altitudes, where high energy intake may allow individuals to forego energetic trade-offs. When applying EBH to poikilotherms, a great emphasis should be placed on total energy intake in addition to energy allocation. Future research on EBH will benefit from more intra-specific comparisons and the evaluation of fitness consequences beyond energy limitation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".