The food-unlimited growth rate of Atlantic cod (<i>Gadus morhua</i>)
Bibliographic record
Abstract
Results from laboratory experiments showed that food-unlimited growth rate (G) of Atlantic cod (Gadus morhua) declined linearly with fish weight (W) on a loglog scale at six different temperatures: 2, 4, 7, 10, 13, and 16°C. The intercept (αi) and slope (βi) of these regressions increased linearly with temperature (T), implying that G = αi W βi, where αi = γ1 + δ1T and βi = γ2 + δ2T. Nonlinear fit of the four-parameter model showed that γ1 was not significantly different from 0, and thus the following three-parameter model is suggested for the food-unlimited growth rate of cod ranging in size from 2 to 5000 g at any temperature from 2 to 16°C: G = (0.5735T)W(0.19340.02001T). The results indicate that temperature in this size range has a much greater effect on the growth rate of small juvenile cod than on that of larger cod. The model predicts that the optimal temperature for growth of cod decreases with increased size of fish, from 14.3°C for 50-g fish to 5.9°C for 5000-g fish. Growth curves were derived for cod at constant and seasonally variable temperatures. Weight-at-age was calculated for different temperatures.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".