ARTHRITIS HEALTH PROFESSIONS ASSOCIATION ccording to Health Canada’s
Bibliographic record
Abstract
publication, there are more than 100 different forms of arthritis and related conditions affecting 4 million Canadians aged 15 or older. These are disorders of the musculoskeletal system- bone, joints, bursae, muscles, and tendons. The prevalence of arthritis among Canadians increases by almost 1 % every 5 years. By the year 2026, about 6 million Canadians, or 20 % of the population aged 15 or older, will be affected, with the largest increases among adults 55 and older. Arthritis is not just a disease of the elderly. Although prevalence does increase with age, 3 out of 5 people with arthritis are younger than 65. Arthritis can be divided in two broad categories. Inflammatory conditions such as rheumatoid arthritis (RA) are characterized by synovial inflammation, which is a swelling of the joint lining (Figure 1). Non-inflammatory conditions include osteoarthritis (OA), which is characterized by cartilage degradation (Figure 2). RA affects 1 to 2 % of the population, with onset occurring mainly in women of childbearing age. OA is present on the X-rays of 80 % of people over 60, but only about one third experience the symptoms. If left untreated, both OA and RA can affect the structure and functioning of the joints, leading to pain and difficulty performing the activities of daily living. Arthritis is the number one cause of long term disability in Canada and one of the most common reasons that people visit their doctors. Compared to people with other chronic diseases, people with arthritis have more pain. They report having to stay in bed and reduce activities more than people with other chronic diseases.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.238 | 0.078 |
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".