Optimizing Time of Initiation for Triploid Walleye Production Using Pressure Shock Treatment
Bibliographic record
Abstract
Abstract Walleyes Sander vitreus support important recreational and commercial fisheries, and have been introduced into many systems throughout the United States and Canada. Use of sterile triploid fish is a valuable management strategy for protecting native fish species from naturally reproducing populations of introduced predators like Walleyes. Hydrostatic pressure is one of the more effective methods for inducing triploidy in Walleyes, and the technique is currently evolving. A 2.7-L capacity electric pressure chamber (TRC-APV Aqua Pressure Vessel; TRC Hydraulics) was used to produce triploid Walleyes using hydrostatic pressure with eggs collected from Pueblo Reservoir, Colorado. The TRC-APV has many advantages over manually operated pressure chambers including its portability, large capacity, and safety. Here, the methods used to create triploid Walleyes using the TRC-APV and the flow cytometric methods for estimating the efficacy of ploidy induction from pooled samples of fry are described. In addition, times of initiation (TIs), the times between fertilization and when eggs were subjected to pressure, were varied to determine the optimal time for maximizing induction and hatching success rates. Results suggest that triploidy in Walleyes is maximized with a TI of approximately 7.5 min, whereas hatching success is maximized with a TI of just over 8 min.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".