Bibliographic record
Abstract
The goal of this diploma thesis is to evaluate the actual performance and actual status of American western breeds in Czech Republic. The statistical analysis is based on data from the Central register of horses, breeders associations and on the results of one of the accredited discipline by ČJF and FEI, reining. The results were collected between the years 2013 and 2015 from ČJFs archive. The analysis uses the GLM, dependent variables were points earned in the competition and placement in the competition, the effects were breed of the horse, age of the horse, year of the competition, level of the competition, the rider and the equestrian association. Also in the case of signification effect was Scheffes and Tukey-B multiple comparison test used. Through the analysis of data mentioned above it was found that the amount of bred western horses in Czech Republic has an increased trend, also their efficiency in reining competitions improves. The most popular breed of western horses bred in Czech Republic is American Quarter horse which is also in reining represented most often, followed by American Paint horse and Appaloosa.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".