Differences in the subgingival microbial composition associated with alcohol intake: A systematic review
Bibliographic record
Abstract
Objectives: This study aimed to conduct a systematic evaluation of the literature on whether individuals exposed to alcohol intake present differences in the subgingival microbial composition compared to those unexposed. Methods: Five databases (MEDLINE, EMBASE, LILACS, SCOPUS and Web of Science) and one source of grey literature (Google Scholar) were searched by two independent reviewers up to December 2022 according to pre-specified eligibility criteria. No restrictions were imposed regarding the date and language of publication and the periodontal status of the participants. The Newcastle-Ottawa Scale was used for methodological quality appraisal and a narrative synthesis was performed. Results: Eight cross-sectional studies and one cross-sectional analysis nested in a cohort were considered for qualitative analysis, including data of 4636 individuals. Overall, the studies exhibited considerable heterogeneity in terms of characteristics of the participants and microbiological methods. Four studies have high methodological quality. Exposed individuals have higher overall quantity of periodontal pathogens in shallow and moderate to deep pockets. Findings on richness, relative abundance, alpha- and beta-diversity were limited and inconclusive. Conclusion: ) bacteria when compared to those unexposed.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".