Meta-analysis of application of autogenous dentin for alveolar ridge augmentation.
Bibliographic record
Abstract
OBJECTIVES: This investigation aimed to systematically evaluate the efficacy and safety of applying autogenous dentin (ATD) in alveolar ridge augmentation. METHODS: The PubMed, Embase, Web of Science, Cochrane Library, CNKI, and Wanfang databases were electronically searched from January 1, 2010 to March 19, 2022 to identify clinical trials and cohort studies that employed ATD in alveolar ridge augmentation. The Cochrane Tool and the Newcastle-Ottawa Scale were employed to assess the risk of bias in randomized controlled trials and cohort studies, respectively. Data were analyzed via RevMan 5.4 software. RESULTS: =0.98]. CONCLUSIONS: ATD, as a bone grafted material for alveolar ridge augmentation, not only achieves similar or better bone incremental performance than autologous bone or DBBM but also has less absorption. However, further evidence from clinical trials with larger samples, higher quality, and longer follow-up period are needed to evaluate its superiority.
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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 | 0.026 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.051 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".