Genetic structure of the carp population (Cyprinus carpio carpio) grown in the aquaculture in the Republic of Belarus
Bibliographic record
Abstract
In this study, we presented a panel of 14 microsatellite loci (MFW1, MFW2, MFW6, MFW9, MFW10, MFW11, MFW13, MFW16, MFW20, MFW24, MFW26, MFW28, MFW29 and Cid0909), with which we studied the genetic structure of Cyprinus carpio carpio of the breed “Izobelinsky” in the Republic of Belarus. Four offshoots of carp were included in the study: two mirrory (“Smes’ zerkal’naya”, “Tri prim”) and two scaly (“Smes’ cheshujchataya”, “Stolin XVIII”). As a result, it was found that the carp breed “Izobelinsky” exhibits a high level of in-breed genetic variability. In the studied microsatellite loci, 231 alleles were identified, 62 % of the total number of alleles were rare alleles with a frequency of occurrence of less than 5.0 %. The number of effective alleles (Ne) at the loci ranged from 3.082 (MFW10) to 9.754 (MFW26). The Shannon biodiversity index (I) was 2.082 ± 0.075. The highest value of the expected heterozygosity index (He) was noted for the MFW26 locus (0.897), the lowest – for the MFW10 locus (0.676). The greatest genetic diversity is characteristic of the scaly carp “Smes’ cheshujchataya” and “Stolin XVIII”. The highest total percentage of rare alleles was determined for fishes from “Stolin XVIII”. The minimum values of this parameter were found for specimens of the carp “Smes’ zerkal’naya” and “Tri prim”. The results of this study indicate a fairly high genetic diversity of four offshoots of the carp breed “Izobelinsky”, which was established using the marker loci optimally selected for analysis. This makes it possible to differentiate the layering among themselves.
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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 | 0.001 |
| 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".