Greening phenomenon in bivalve by marennine produced from Haslea ostrearia and its consequences on bivalve’s integrated response
Bibliographic record
Abstract
This Ph.D. thesis focuses on several assessments to achieve the optimum benefit of utilization of marennine in the field of aquaculture. The study covers: (1) the assessment in feeding behavior of the Pacific oyster Crassostrea gigas on different sizes of Haslea ostrearia and its ecological consequence; (2) the characterization of the greening by marennine and its consequences on some physiological traits of on C. gigas. (3) the consequence of greening by marennine on behavioral, physiological and biochemical traits of bivalves; (4) the utilization of H. ostrearia and marennine in a combination diet with other microalgae relevant to aquaculture.Our results suggest that cell size impacts considerably the selection process of H. ostrearia by oyster. This study also demonstrates that the extracellular form of marennine contributes significantly to the greening in the mucocytes of the gills. Apart from greening the pallial organs of bivalves, marennine (2 mg L-1) affects the behavioural, physiological and biochemical performance. Nevertheless, these effects can be compensated for its biological activities such as natural antibacterial agent and use as a mixed algal diet for bivalve aquaculture.
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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".