Chronic oedema/lymphoedema: under‐recognised and under‐treated
Bibliographic record
Abstract
Even though it is estimated that at least 300 000 people in Canada may be affected by chronic oedema/lymphoedema, recognition of the seriousness of this chronic disease in health care is scarce. Lymphoedema affects up to 70% of breast and prostate cancer patients, substantially increasing their postoperative medical costs. Adding to this problem are the escalating rates of morbid obesity across North America and the fact that 80% of these individuals are thought to suffer with an element of lymphoedema. The costs related to these patient populations and their consumption of health care resources are alarming. Untreated chronic oedema/lymphoedema is progressive and leads to infection, disfigurement, disability and in some cases even death. Thus, prognosis for the patient is far worse and treatment is more costly when the disease is not identified and treated in the earlier stages. Although the number of individuals coping with chronic oedema/lymphoedema continues to increase, the disparity between diagnosis, treatment and funding across Canada endures. The reasons for this include a lack of public awareness of the condition, insufficient education and knowledge among health care providers regarding aetiology and management and limited financial coverage to support appropriate methods and materials.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".