Estimating consumable biomass from body length and order in insects and spiders
Bibliographic record
Abstract
1. Current models used to estimate insect prey biomass for diet studies use whole weight. However, a large proportion of an arthropod's body is taken up by an indigestible exoskeleton, leading to erroneous estimation of the food intake of insectivorous animals. 2. Linear mixed effect models were used to obtain equations to predict consumable biomass from body length for a variety of N eotropical insects and spiders. These data were obtained by feeding taxa of various orders to groups of 100 social spiders and comparing pre‐ and post‐consumption weights using size‐matched controls. 3. Significant linear relationships were found relating body size to consumed biomass for all orders, with slopes ranging from 1.276 to 4.011 and R 2 values from 0.476 to 0.929. For orders other than spiders and O rthoptera, the increase in weight with size exhibited negative allometric scaling, suggesting a decrease in tissue density, or an increase in internal air space, with size. 4. Although there were significant differences across taxonomic orders in the proportion of biomass consumed, within most orders the proportion consumed did not differ significantly with body size. The estimated regression coefficients may be used by other workers to estimate consumable biomass of arthropod prey for studies requiring large sample sizes or non‐lethal sampling of rare or endangered species.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".