Alternative model structures for bioenergetics budgets of a cruising predatory gadoid: incorporating estimates of food conversion and costs of locomotion
Bibliographic record
Abstract
Swimming costs of North Sea saithe (pollock) (Pollachius virens) were estimated from a balanced energy budget equation using field estimates of food ration and growth together with two alternative food conversion functions. Food ration estimates were obtained by application of a gastric evacuation model to field data on amount and composition of stomach contents. Laboratory-based net conversion efficiency, κlab, produced values of 1.616.72 of the activity multiplier, whereas estimates of 1.443.27 were obtained from application of an activity-modulated net conversion efficiency, κwild. The activity multiplier ranged from 2.0 to 2.5 at optimum cruising speed. The high activity levels obtained by application of κlab probably reflect low-cost accumulation of lipid in laboratory saithe. All together, the results indicated that net conversion efficiency in North Sea saithe was better described by κwild (ranging from 0.43 to 0.50) as opposed to κlab (0.510.76). Model estimates of food ration and body growth using activity costs at optimum cruising speed further demonstrated the sensitivity of estimates from the balanced energy budget equations to applied parameter values and field estimates of variables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".