Development of a core measurement set for research in degenerative cervical myelopathy: a study protocol (AO Spine RECODE-DCM CMS)
Bibliographic record
Abstract
INTRODUCTION: Progress in degenerative cervical myelopathy (DCM) is hindered by inconsistent measurement and reporting. This impedes data aggregation and outcome comparison across studies. This limitation can be reversed by developing a core measurement set (CMS) for DCM research. Previously, the AO Spine Research Objectives and Common Data Elements for DCM (AO Spine RECODE-DCM) defined 'what' should be measured in DCM: the next step of this initiative is to determine 'how' to measure these features. This protocol outlines the steps necessary for the development of a CMS for DCM research and audit. METHODS AND ANALYSIS: The CMS will be developed in accordance with the guidance developed by the Core Outcome Measures in Effectiveness Trials and the Consensus-based Standards for the selection of health Measurement Instruments. The process involves five phases. In phase 1, the steering committee agreed on the constructs to be measured by sourcing consensus definitions from patients, professionals and the literature. In phases 2 and 3, systematic reviews were conducted to identify tools for each construct and aggregate their evidence. Constructs with and without tools were identified, and scoping reviews were conducted for constructs without tools. Evidence on measurement properties, as well as on timing of assessments, are currently being aggregated. These will be presented in phase 4: a consensus meeting where a multi-disciplinary panel of experts will select the instruments that will form the CMS. Following selection, guidance on the implementation of the CMS will be developed and disseminated (phase 5). A preliminary CMS review scheduled at 4 years from release. ETHICS AND DISSEMINATION: Ethical approval was obtained from the University of Cambridge (HBREC2019.14). Dissemination strategies will include peer-reviewed scientific publications; conference presentations; podcasts; the identification of AO Spine RECODE-DCM ambassadors; and engagement with relevant journals, funders and the DCM community.
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How this classification was reachedexpand
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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".