Bibliographic record
Abstract
Canine arthritis is a common and complex disease with many influencing factors and proper treatment remains clouded among the pharmaceutical treatments available. This study was carried out with the objectives of obtaining a further understanding for the factors influencing this disease, but also to analyze the efficacy of pharmaceutical treatment, comparing between two specific medications, Cartrophen and Librela. The study was conducted at an anonymous Small Animal Clinic in Sweden, Clinic X. 28 dogs of mixed gender, breed and age were reviewed from the clinic´s computerized system, collected from 2018 to 2022. The dogs had either been previously diagnosed with arthritis or were suspected of having arthritis. All 28 dogs were analyzed in this study. It was found that many dogs diagnosed with osteoarthritis, the most common type, in this study were females, were of an older age and had a Body Condition Score (BCS) above the ideal BCS of 5/9. The most frequent breed presented in this research was Labrador Retriever. The most common symptom noted from dog owners was pain and limping. Most of the dogs were initially treated with NSAIDs, but all were further treated with either Cartrophen or Librela around 1 month after the beginning of treatment. The choice of treatment was changed for a number of the dogs during the treatment period, from Cartrophen to Librela or the other way around, as some owners reported no response to initial treatment. It was additionally found that many dogs required continuous treatment of NSAIDs in conjunction with either Cartrophen or Librela. It could be concluded that no significance was found between the factors influencing osteoarthritis nor their effect on the disease, and the results obtained in this research follows most results obtained in previous studies. However, some recent studies still prove that further and more thorough analysis needs to be performed to truly understand the factors influencing this disease as well as their effect on the disease development. It can also be concluded that Librela poses as a pharmaceutical drug of great potential to become a standard treatment for arthritis.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.028 |
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".