Update to the PRISMA guidelines for network meta-analyses and scoping reviews and development of guidelines for rapid reviews: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review is to develop a list of items for potential inclusion in the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) reporting guidelines for network meta-analysis (NMA), scoping reviews (ScRs), and rapid reviews (RRs). INTRODUCTION: The PRISMA extensions for NMA and ScRs were published in 2015 and 2018. However, since then, their methodologies and innovations, including automation, have evolved. There is no reporting guideline for RRs. In 2020, an updated PRISMA statement was published, reflecting advances in the conduct and reporting of systematic reviews. These advances are not yet incorporated into these PRISMA extensions. We will update our previous methods for scoping reviews to inform the update of PRISMA-NMA and PRISMA-ScR as well as the development of the PRISMA-RR reporting guidelines. INCLUSION CRITERIA: This review will include any study design evaluating the completeness of reporting, offering reporting guidance, or assessing methods relevant to NMA, ScRs, or RRs. Editorial guidelines and tutorials that describe items related to reporting completeness will also be eligible. METHODS: We will follow the JBI guidance for scoping reviews. For each PRISMA extension, we will i) search multiple electronic databases from inception to present, ii) search for unpublished studies, and iii) scan the reference lists of included studies. There will be no language limitations. Screening and data extraction will be conducted by 2 researchers independently. A third researcher will resolve discrepancies. We will conduct frequency analyses of the identified items. The final list of items will be considered for potential inclusion in the relevant PRISMA reporting guidelines. REVIEW REGISTRATION: NMA protocol (OSF: osf.io/7bkwy ); ScR protocol (OSF: osf.io/7bkwy ); RR protocol (OSF: osf.io/3jcpe ); EQUATOR registration link: https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-systematic-reviews/.
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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 | 0.414 | 0.565 |
| Meta-epidemiology (narrow) | 0.005 | 0.009 |
| Meta-epidemiology (broad) | 0.011 | 0.026 |
| Bibliometrics | 0.023 | 0.023 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.009 | 0.018 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.101 | 0.055 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".