Temperature affects growth allometry and development patterns in brown trout (<i>Salmo trutta</i>) fry: a multitrait approach
Bibliographic record
Abstract
To study the influence of temperature (4, 6, and 12 °C) on the development of brown trout (Salmo trutta) from hatching to the end of metamorphosis, an analysis of allometric growth patterns was conducted to identify two different groups of individuals, namely developmental phases at total lengths (TL) ranging from 2.72 cm at 4 °C to 2.22 cm at 12 °C. Then, a multitrait approach considering different variables like the survival rate, development time, morphometric characteristics, energetic value, and skeletal mineralization was conducted on these two groups. Results indicated that the first growth phase was slower at 4 °C, whereas the second was also slower at this temperature, even though swimming behavior was already present. However, at 12 °C, fry showed a delay in their development (i.e., lower levels of skeletal mineralization and energetic content) during the first growth phase, but they compensated during the second growth phase, reaching the same size in TL when compared with the other temperatures (4 and 6 °C); fry at 12 C° showed low energy reserves. Our study demonstrated that the use of an allometric analysis to identify different developmental stages coupled with a multitrait approach was more efficient than a classical distinction between biological stages (hatching, emergence, first food intake, and exogenous feeding), and this procedure is of interest when evaluating the impact of rearing conditions on early development in fish.
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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 | 0.001 | 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) | 0.001 | 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".