Scaling of the extended phenotype: convergent energetics from diverse spider web geometries
Bibliographic record
Abstract
Organisms capture energy to support growth, survival and reproduction in diverse ways. Larger metazoans require less energy per unit time and mass than smaller ones. Thus, structures animals build to capture energy need not scale isometrically with body size. Web-building spiders use silk structures of diverse geometries to capture energy, including two-dimensional orbs in some families or three-dimensional tangles or sheet-and-tangles, in others. Despite this diversity, we show that energy consumption rate per unit mass scaled identically with body size across all web geometries with a less than 1 : 1 relationship to body size, as expected for metazoans from metabolic theory. Spiders thus appear to adjust the size and shape of their webs in precise ways to attain this relationship, including, as we show here, creating a hollow space within certain three-dimensional web types to maintain a constant prey capture surface area per unit spider mass as they grow in size without requiring more silk. Our findings show how the allometric relationship between energetic traits and body size can be mediated by extended phenotypes and suggest an equivalence paradigm akin to the equal fitness paradigm whereby the diverse adaptive strategies of organisms allow them to perform equally well in supplying a unit of mass the energy needed across a lifetime.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".