Red blood cell indices of rainbow trout Oncorhynchus mykiss (Walbaum) in aquaculture
Bibliographic record
Abstract
A direct non-parametric method was used to calculate reference (physiological) haematology values for farmed 10–12-month rainbow trout of the Kamloops strain (mean weight: 330±131 g) with respect to red blood cell counts (RBCc), haematocrit values (Hct), haemoglobin concentrations (Hb), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH) and mean corpuscular haemoglobin concentrations (MCHC). The fish in the selected reference group (n=798) were given dry pelleted diets that contained 37–47% crude protein, 7–18% crude fat and 108–300-mg vitamin E, 1.08–5-mg folic acid, 0.018–0.05-mg vitamin B12, 48–64.5-mg iron, 4.5–8.4-mg copper and 0.18–0.24-mg selenium supplied per kg of diet. Ethoxyquin and butylhydroxytoluol were used to protect the fat component against oxidation. The fish were kept at a stocking density of 50kg per cubic metre in tanks provided with running freshwater (dissolved oxygen 8.4–11.5 mg L−1, with O2 saturation of 77–98%) at an ambient temperature of 0.2–16°C. Blood was sampled between September and November at a photoperiod of 9–13 h:11–15 h (light:dark). Reference ranges for the preceding haematological indices were as follows in immature females (males): RBCc, 0.77–1.42T L−1 (T – tera, 1012) (0.98–1.55T L−1); Hct, 0.304–0.502 (0.34–0.546); Hb, 54–93 g L−1 (59–97 g L−1); MCV, 282–469 fL (279–434 fL); MCH, 51–86 pg (47–78 pg); MCHC, 0.15–0.22 (0.15–0.2). In males, values for RBCc, Hct and Hb were significantly higher (P=0.01 and 0.0000 respectively) and those for MCV, MCH and MCHC were significantly lower (P=0.01 and 0.0002 respectively) than in immature females. Nutritional and environmental factors affecting erythropoiesis in trout and some correlations between haematological (RBCc, Hb, Hct) and biochemical indices of the blood plasma (total protein, cholesterol) are discussed.
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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 | 0.001 | 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".