A novel Osteoarthritis scoring system to separate typical OA joint degeneration from non-typical lesions in male Sprague Dawley rats
Bibliographic record
Abstract
Objective: To develop a novel scoring system to characterize osteoarthritis-related degeneration distinct from spontaneous subchondral bone lesions observed in the tibia and femur of male Sprague Dawley rats. Method: Knee joints from male rats following 12 weeks of a diet-induced obesity model of osteoarthritis (OA) were assessed. OA histopathological changes (OAHC) were assessed in the knee joints. All scores were evaluated using a modified Mankin score and a modified Osteoarthritis Research Society International histological score. OAHC were divided into 3 categories: (I) Typical OA score evaluating the changes in cartilage structure, cellularity, proteoglycan depletion, and tidemark integrity, (II) A novel Non-typical OA score evaluating cartilage integrity, and the size of local thickening, fragmentation and degeneration along the tidemark and the size and severity of the subchondral bone lesion, and (III) Total OA score comprised of both, the Typical and the Non-typical scores. Results: Rats exposed to a high fat/high sucrose diet had higher Typical OA score compared to a control group (Chow). Non-typical and Total OA scores revealed no differences in the severity of the lesions between the HFS and the Chow group animals. All scoring systems had excellent intra- and inter-examiner reliability. Conclusion: The spontaneous bone lesions observed in male Sprague Dawley rats can obscure the effect of the diet-induced obesity if the classical scoring system is used to assess joint degeneration. The newly proposed scoring method provides a reliable method to distinguish classical OA joint degeneration from spontaneous Non-typical lesions occurring in these rats.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".