Bibliographic record
Abstract
Osteoarthritis (OA) is a common, chronic, musculoskeletal disease. It is the most common form of arthritis and its prevalence increases with age. It is also referred to as degenerative joint disease and is characterized by cartilage degeneration with reactive new bone formation at the joint margins. This degeneration and new bone formation result in pain and stiffness in the affected joints{.1} OA has traditionally been considered a passive process of joint wear and tear. However, it is now considered a metabolically active process with both anabolic and catabolic activity.1 Commonly affected joints are the hands, knees, hips, and cervical and lumbar spine, and OA is often associated with significant disability and impaired quality of life. . Risk factors include age, sex, ethnicity, genetic profile, hormonal status, bone mineral density (BMD), and nutritional factors. Obesity, joint injuries and deformities, sports participation, muscle weakness, and occupational factors are also associated with OA. There is no known cure. Management goals include reducing pain and maintaining or improving joint function. Treatment of OA is broadly divided into pharmacological and non-pharmacological treatments. Exercise, patient education, telephone support, and weight reduction are safe non-pharmacological approaches. Pharmacological treatment includes paracetamol, non-steroidal anti-inflammatory drugs, intra-articular therapy, and surgical treatment. Dietary and lifestyle interventions have received insufficient attention
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".