Vlivy na výkon psa ve vrcholových soutěžích agility
Bibliographic record
Abstract
This bachelor thesis deals with the use of a dog and dog sports. It is concentrated on the dog sport called agility, on the history of this sport and its regulations in the Czech Republic. It mentions races used in agility and their specific characteristics for this kind of dog sport. There were 1266 specimen studied in total, in three size categories. These categories are small, medium and large. and they are determined according to the shoulder height of the dog. For the analysis, the results from the Championships of the Czech Republic in the years 2010 till 2016 were used. The influence of gender, age and race on the final result was determined. On the basis of a detailed study and analysis, it was found out, that the most suitable dogs for participating in these races with the best results are in the category small and medium sheltie (37 %, resp. 23 %) and in the category large border collie (68 %) and belgian shepherd (9 %). Comparing the results in the competitions regarding the gender, bitches were always more succesful than dogs. As for the age, the dogs in the category small between the 5th and 7th year , in the category medium between the 5th and 6th year and in the categoty large between the 4th and 6th year achieved the best results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".