RESEARCH ARTICLE Clinical validity of outcom
Bibliographic record
Abstract
tin ro Background clinical and radiographic finding in dog OA is well recog-Rialland et al. BMC Veterinary Research 2012, 8:162 http://www.biomedcentral.com/1746-6148/8/162designed for OA and chronic pain has evolved over time(CRCHUM), Notre-Dame Hospital, Montreal (QC) H2L 4 M1, Canada Full list of author information is available at the end of the articleThe prevalence of osteoarthritis (OA) in the canine population (20 % of adult and 80 % of the geriatric (> 8 years old) dogs in North America [1]) makes the disease a major cause of concern. The distortion between nized [2]. The symptomatic signs of OA are highly vari-able, related to pain and physical functioning, and translated into limb impairment, activities limitations and restricted participation [3-5]. This situation led to the use of multiple methods to assess the efficacy of OA treat-ment [6]. However, interpretations are not always clear, the results are often inconsistent and clinical validation of these methods is often missing. The conceptual validitya of the canine pain scales
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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 | 0.014 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".