Internet-Based Survey on Physical Activity and Incidence of Injury in Active Working Dogs
Bibliographic record
Abstract
A survey with 100 multiple choice and open-ended questions was proposed by free access to working dogs' handlers. One hundred and nine respondents were recorded and their dates processed. The most represented breeds were: Belgian Malinois, Labrador, Border Collie and German Shepherds. Of these, 71.6% were intact dogs and 28.4% were spayed or neutered, with a median age range of 3-4 years. Furthermore, 55.5% had undergone early radiographic examinations for hip or elbow dysplasia diagnosis. The dogs performed the following activities: search and rescue on surface (59%), search and rescue on rubble (37%), Internationale Gebrauchshund Pruefung (IGP) (9%), man trailing (5%), sled dog (5%), search on avalanche (4%), dog towing (3%), canine shows (3%), hunting (2%), water rescue (1%), pet therapy (1%), wildlife conservation dog (1%), Mondioring (1%). Only 36.4% of respondents submitted their dogs to a specific sports medical examination and 55.5% to an orthopaedic examination. An injury incidence of 45.5% was recorded, generally related to mild musculoskeletal trauma. A limited number of handlers routinely performed warm-up and/or cool-down activities. A positive assessment emerged of the need for many respondents to attend and request education courses and updates on the proper health management of their dogs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.003 | 0.001 |
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".