The combination of bivariate and multivariate methods to analyze character synchronization and early allometric growth patterns in the stellate sturgeon (<i>Acipenser stellatus</i>) as tools for better understanding larval behavior
Bibliographic record
Abstract
Multivariate allometry patterns and length at metamorphosis (Lm) were determined in Acipenser stellatus by means of principal component analysis from 12 morphometric characters. The multivariate analysis differentiated three growth stanzas: the prelarval, larval, and early juvenile stages. The prelarval stage comprised the period from hatching (9.7 mm in total length, TL) to the transition to exogenous feeding (17.7 mm TL, Lm1), a period characterized by yolk sac depletion and fast growth of the anterior and posterior body regions. These changes coincided with the development of sensory, feeding, respiratory, and swimming systems to improve foraging behavior and predator avoidance. During the larval period (17.7–52.8 mm, Lm1–Lm2), specimens reached a juvenile phenotype characterized by the development of median fins, elongation and flattening of the snout and formation of bony scutes, and the improvement of their swimming capacities, allowing larvae to regulate their dispersal distance from the spawning grounds. The end of the larval period and acquisition of the juvenile phenotype were found after Lm2 when some variables reached isometry or even displayed a negative allometric growth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".