A computational model for asynchronous oocyte growth dynamics in a batch-spawning fish
Bibliographic record
Abstract
A computational model of oocyte growth dynamics (i.e., oocyte recruitment, growth, and spawning) in a batch-spawning fish, fathead minnow (FHM, Pimephales promelas), has been developed. The model provides a quantitative link between oocyte growth dynamics and biochemical processes in FHMs through the absorption of vitellogenin (a lipoprotein precursor of egg yolk proteins) into oocytes, which contributes significantly to oocyte growth in fish. The model simulates the number and volume of oocytes in different batches within a FHM ovary. Model-predicted clutch sizes and spawning intervals matched the experimental data well for both unexposed FHMs and FHMs exposed to 17β-trenbolone (a relatively stable metabolite of trenbolone acetate, a synthetic androgen used as a growth promoter in livestock). Overall, the model presents a novel approach to simulating oocyte growth dynamics in a batch-spawning fish and meets an urgent need in ecotoxicological studies to link the effects of endocrine disrupting chemicals at a biochemical level to adverse effects upon reproduction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".