Development of an online registry for adults with arthrogryposis multiplex congenita: A protocol paper
Bibliographic record
Abstract
Arthrogryposis multiplex congenita (AMC) is considered a rare disorder resulting in multiple congenital contractures in two or more areas. Considerable literature is available on managing the contractures during an affected child's development but little information is available to those managing these ongoing issues in adulthood. Due to the heterogeneity etiological factors and presentation of AMC, and the small sample sizes of previous studies, it has been difficult to generalize results to the adult population. This current study presents the several steps taken to create an international AMC database for adults to populate with their own data over time. The methods included a scoping review of the literature for valid and reliable outcome measures used for AMC, a Delphi methodology to create the database with a team of clinicians, researchers and patients, a Beta testing of the database, and a final launch of the Adult AMC Registry. This registry includes 48 nonstandardized questions and 12 standardized questionnaires. It takes 35-45 min for a participant to complete. A shorter version will be created for participants to complete for years 2 and 3, followed by this longer version every 4 years. The protocol for referring English-speaking patients and access to the registry is provided. Data will be reviewed every year to ensure quality. The registry will be maintained for a minimum of 10 years and data will be comprehensively analyzed every 5 years. Our goal is to have 500 adults with AMC from around the world as participants.
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 | 0.161 | 0.154 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.059 | 0.019 |
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".