The application of medical scale in the treatment of plantar warts: analysis and prospect
Bibliographic record
Abstract
Plantar warts are common cutaneous diseases on the sole caused by the human papillomavirus, with a high annual incidence rate of 14%. It often causes pain, which impairs quality of life of patients. Numerous therapeutic options for plantar warts exist with variable success. However, all of them, including first-line treatment, have different adverse reactions or high recurrence rates. There is no one effective method for all patients. The choice of treatment method puzzles doctors. With the help of medical scales, we can analyze the patients' condition, so as to guide the choice of treatment methods, which is of great significance for the individualized treatment of patients with plantar warts. This review takes cryotherapy, intralesional injection of bleomycin and photodynamic therapy as examples to discuss the application of medical scales in the treatment of plantar warts, summarizes the scales that can be used to evaluate the status of plantar wart, adverse reactions, prognosis and patient's financial situation, and discusses their clinical and scientific value. We hope to use scales to consider the severity of plantar warts and economic level, help different patients to choose different treatment options, and make suggestions on the evaluation of the adverse reactions and treatment effect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".