Embryonic and larval development of yellow perch (<i>Perca flavescens</i>) and its sensitivity to incubation temperature
Bibliographic record
Abstract
The ontogenetic development in teleost fish is sensitive to temperature, and the developmental rate has a direct relationship with the environmental temperature within a species' thermal tolerance limit. Temperature determines time to and survival at hatching. Yellow perch is a North American species of ecological and commercial importance, and its phenology is vulnerable to climate change. The embryonic development of yellow perch was comparable to closely related members of the family Percidae. Developmental progression was fastest at 18°C and slowest at 12°C, with medial progression at 15°C. Time to hatch and swim-up, feeding onset, and exogenous feeding phases were different across all incubation temperatures regardless of a gradual post-hatch warming of the 12 and 15°C groups to a common garden temperature of 18°C. Incubation temperature may lower the rate of survival to hatch at 15°C and had complex impacts on developmental abnormalities. Temperature had significant effects on the development rate, time of hatch, survival, and incidence of developmental abnormalities. Early ontogenetic thermal history in ectotherms is an important factor determining phenotypic variation. It will be important to link the thermally induced changes in development described here to the physiological and morphological differences and to link the developmental abnormalities to functional performance.
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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) | 0.001 | 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".