A generic model to estimate food consumption: linking von Bertalanffy’s growth model with Beverton and Holt’s and Ivlev’s concepts of net conversion efficiency
Bibliographic record
Abstract
In this paper, a mathematical derivation is presented that links von Bertalanffy’s growth model with the concept of net conversion efficiency of Beverton and Holt, aiming at the development of an equation that can calculate food consumption rates of wild populations from parameters of the von Bertalanffy growth equation and an estimate of the net food conversion efficiency of Beverton and Holt. The derivation is based on Pauly’s version of the generalized von Bertalanffy equation, which allows the allometric exponent of the anabolism term to differ from 2/3, as in the standard von Bertalanffy equation. As a side product, a general model is formulated that describes the gross growth conversion efficiency (K1 of Ivlev) as a function of weight of the organism. The new equations for the estimation of food consumption are applied in two case studies, North Sea cod ( Gadus morhua ) and whiting ( Merlangius merlangus ), for which a variety of consumption estimates is available from conventional gastric evacuation-based methods. The new method produces results that show a similar degree of variability as was observed in various applications of the gastric evacuation method.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".