Expanding Data Collection for the <scp>MDSGene</scp> Database: X‐linked Dystonia‐Parkinsonism as Use Case Example
Bibliographic record
Abstract
MDSGene is an online database on movement disorders that collates genetic and clinical knowledge using a standardized published literature abstraction strategy. This review is dedicated to X-linked dystonia-parkinsonism (XDP). We screened 233 citations and curated phenotypic and genotypic data for 414 cases. To reduce data missingness, we (1) contacted authors and engaged the research community to provide additional clinical and genetic information, and (2) revisited previously unpublished data from a cohort of XDP patients seen at our institution. Using these approaches, we expanded the cohort to 577 cases and increased information available for important clinical and genetic features such as age at onset, initial manifestation, predominant motor symptoms, functional impairments, and repeat size information. We established the use of mining unpublished data to expand the MDSGene workflow and present an up-to-date description of the phenomenology of XDP using an extensive collection of previously reported and unreported data. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.012 |
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".