Implementation of the Current Dystonia Classification from 2013 to 2018
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There is a discrepancy in the way dystonia is classified in the literature, as articles continue to reference the old criteria or fail to use the 2013 criteria correctly. METHODS: We performed a systematic review of the dystonia literature and distinguished between studies that use the new classification correctly, made errors in implementing the new classification, or continued to use the old classification methods. RESULTS: Of the 990 articles included in the study, 59.8% used the classification correctly, 31.3% used mixed terminology, and 8.9% continued to use the old classification. Articles relating to surgery were significantly less likely to use the new classification correctly. There is an upward trend in the annual rate of articles properly referencing the new classification. CONCLUSIONS: The 2013 classification has been well received in scientific literature, and more studies are adapting to its use.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it