Genetic characterization of four strains of Nile tilapia (<i>Oreochromis niloticus</i> L.) using microsatellite markers
Bibliographic record
Abstract
Four domesticated strains of Nile tilapia (Oreochromis niloticus L.) were genetically characterized using 14 microsatellite markers and 64 animals per strain. Two strains, Chitralada (AIT) and International Development Research Centers (IDRC) were obtained from the AIT institute, Bangkok, Thailand. The GIFT strain (5th generation) came from NAGRI, Thailand, and the GOTT strain was supplied by the University of Göttingen, Germany. The average numbers of alleles per marker were 5.0 (GOTT), 5.4 (AIT), 5.6 (IDRC) and 7.5 (GIFT). Private alleles were found at all markers with the exception of two. No fixation of alleles was found at any marker. Population differentiation, FST, was 0.178 (great genetic differentiation) and confirmed grouping of the animals in strains. The expected level of heterozygosity ranged from 0.624 to 0.711, but the observed level of heterozygosity significantly deviated from the expected level in three strains. This was probably because of small population size. Moderate to great genetic differentiation was found between strains. A phylogenetic tree reflected the strains known histories. Application of the Weitzman approach showed that all strains have added value for the total genetic diversity and thus should be retained.
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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) | 0.000 | 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 | 0.001 |
| 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".