Characteristics of systematic reviews published in dentistry by Brazilian corresponding authors
Bibliographic record
Abstract
OBJECTIVE: This study aimed to analyze the reporting and conduct characteristics of systematic reviews (SRs) published in dentistry by Brazilian corresponding authors and compare reporting characteristics of Brazilian SRs with the rest of the world. METHODS: A search in PubMed was performed to identify SRs published in dentistry in 2017 assessing different aspects of oral heath irrespective of the design of included studies. From this dataset, a subgroup analysis was performed considering only SRs published by Brazilian corresponding authors. Study screening was performed by two researchers independently, while for data extraction, one of three reviewers extracted details related to reporting and conduct of SRs. The completeness of reporting of 24 characteristics, included in the PRISMA Statement of the SRs classified as treatment/therapeutic, was evaluated comparing Brazilian SR to SRs from all other countries. RESULTS: We included 117 SRs with Brazilian corresponding authors. The majority focused on dental treatments (39.3%), with oral surgery (n=19, 16.2%) as the most commonly published. Included SRs presented varying reporting/conduct characteristics. Items such as use of reporting guidelines and screening method used were well reported. However, most SRs did not assess the risk of publication bias and did not use the GRADE assessment. Four (of 24) reporting characteristics of Brazilian SRs compared to SRs from the rest of world were reported statistically significantly more frequently: mention of a SR protocol, trial registry searched, screening method reported, and assessment of risk of bias/quality of studies. CONCLUSION: Reporting and conduct characteristics of Brazilian SRs are highly variable.
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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 | 0.141 | 0.577 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.045 | 0.054 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".