Nonoperative management of degenerative cervical radiculopathy: protocol of a systematic review.
Bibliographic record
Abstract
Background: Degenerative cervical radiculopathy (DCR) is a common condition which, due to the aging global population, is expected to worsen over time. For the majority of patients with DCR, surgical intervention is not required as nonoperative management is sufficient for symptom improvement. However, there are significant gaps within the literature as the majority of past systematic reviews assessing conservative interventions are outdated, or omit relevant studies due to strict inclusion/exclusion criteria. Therefore, an updated understanding of the effectiveness of noninvasive nonoperative management for DCR is required. Methods: We will search MEDLINE, CENTRAL, Embase, PsycINFO, and CINAHL from inception, as well as hand-search reference lists of included studies and previous systematic reviews, to identify peer-reviewed randomized controlled trials on this topic. Discussion: The results of this review will provide an understanding of the effectiveness of various nonoperative interventions. The quality of evidence will also be assessed using the GRADE approach. Systematic review registration: PROSPERO CRD42021249699.
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 | 0.073 | 0.081 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".