Chinese Hemophilia Joint Health Score 2.1 reliability study
Bibliographic record
Abstract
To meet the rapidly expanding need for musculoskeletal (MSK) specialists [physiotherapists (PTs), physiatrists] in haemophilia care in China, a 4-day Train the Trainer workshop was conducted in July/August 2009 in Beijing. A key focus was to train the participants to administer the Hemophilia Joint Health Score (HJHS) version 2.1 for effectively evaluating the MSK health of boys <18 years of age with haemophilia. The aim of this study was to test the HJHS version 2.1 inter- and intra-rater reliability in a group of Chinese PTs and physiatrists with limited experience in haemophilia care. Each of the trained Chinese physiatrists and PTs examined eight boys 4-17 years old with moderate and severe haemophilia on day 1 and repeated the examination on the same patients the next day using the HJHS version 2.1. The boys had a wide range of target joint involvement and arthropathy. The HJHS score sheet, work sheets and manual had been translated into simple Chinese prior to the study. The interrater (ICC 0.90) and intra-rater (ICC 0.91) reliability was excellent. The internal consistency of the HJHS items was also excellent with Cronbach's alpha of 0.86. With basic training in the administration of the HJHS version 2.1, the tool was reliably administered by Chinese PTs and physiatrists with limited haemophilic experience.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".