Structured review of enamel erosion literature (1980–1998): a critical appraisal of experimental, clinical and review publications
Bibliographic record
Abstract
OBJECTIVE: To attain an objective account of the methods to measure enamel erosion used in 1980-1998 publications, a structured review of the literature was undertaken. METHODS: Inclusion and exclusion criteria were applied to 731 clinical/experimental research and review reports. Eighty-five included papers were subsequently rated according to 'hierarchy of evidence' guidelines to assess the strength of the report's design and the relevance of the evidence to replicating enamel erosion in vivo in humans. Scores were assigned to rate each aspect in the guidelines. RESULTS: A total of 16 clinical, 13 review and 56 experimental papers were assessed; 36.4% were published during 1996-1998. Excluding reviews, 16 papers were qualitative and 56 quantitative; 51 used human enamel. Our classification yielded nine groups of methods (five scoring systems and 26 measurement techniques). CTFPHE (Can Med Assoc J 1992; 147: 443) grading of research reports indicated that 2.8% provided evidence grade I; 20.8%, grade IIa; 63.9%, grade III; and 12.5%, grade IV. CONCLUSIONS: There has been a consistent increase in the body of knowledge. The overall quality of publications has not substantially changed over time. Experimental studies were more often quantitative, and quantitative studies had better research designs. No single group of research methods had obviously superior research designs.
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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 | 0.060 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.030 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".