Inter- and intra-genetic diversity in the Polish Konik horse: implications for the conservation program
Bibliographic record
Abstract
The main objective of the study was to determine the genetic diversity in the Polish Konik (PK) population in the context of a currently conducted conservation program. A total of 94 horses of 16 PK dam lines currently distinguished by breeders were considered. Pedigree analyses were carried out for the whole population of PK registered in the studbook. Basic molecular parameters were estimated. The average group linkage clustering method was used based on the Euclidean similarity measurements between the lines. The allele frequency of 17 microsatellites was used to determine Euclidean distances. Inbreeding coefficients were extracted from the additive relationship matrix. Moreover, some pedigree parameters were estimated. The observed heterozygosity ranged from 0.48 to 0.76. The expected heterozygosity estimated for the dam lines was higher. PIC values were higher than 0.6 in all the lines. Fis ranged from –0.19 to 0.28, whereas Fit and Fst varied between 0.12 and 0.41 and 0.12 and 0.29, respectively. Minor dissimilarity distances existed for some dam lines. The inbreeding level was 9.3%. The average number of discrete generation equivalents reached 6.85. The majority of the dam lines are not genetically differentiated. Hence, a revision of the breeding strategy seems to be necessary.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".