Effect of nanobubbles (oxygen, ozone) on the Pacific white shrimp (Penaeus vannamei), Vibrio parahaemolyticus and water quality under lab conditions
Bibliographic record
Abstract
This study assessed the effects of oxygen and ozone nanobubbles on gill morphology, weight gain, and mortality of Pacific white shrimp (Penaeus vannamei), as well as the level of Vibrio parahaemolyticus and water quality of shrimp culture tanks under lab conditions. Two experiments were carried out with oxygen macrobubble, ozone macrobubble, oxygen nanobubble, ozone nanobubble, and control treatments (air-stone macrobubble). Experiments were done in triplicate in 100 L tanks with 15‰ saline water, and 20 shrimp per tank. Tanks in Experiment 1 were not inoculated with bacteria; tanks in Experiment 2 were inoculated with V. parahaemolyticus at a concentration of 106 CFU/mL. The results revealed that short treatments with ozone nanobubbles had minimal impact on shrimp gills, mortality, and growth rates, reduced V. parahaemolyticus concentration in water compared to the other groups, and improve water quality. These laboratory results indicate that ozone nanobubble treatment may be useful for controlling V. parahaemolyticus. More work is needed to find the best protocol to apply the technology on a commercial scale.
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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".