Efficiency and effectiveness evaluation of three glass fiber post removal techniques using dental structure wear assessment method
Bibliographic record
Abstract
AIM: This study evaluated the efficiency and effectiveness of three glass fiber post removal techniques. MATERIALS AND METHODS: Forty-five extracted maxillary teeth were endodontically treated and cross-sectioned in thirds. Presence of cementing agent and dental structure wear were assessed by analyzing images taken before luting of glass fiber post and after removal procedure. Teeth were divided into 3 groups: Group 1 - diamond bur + Largo reamer; Group 2 - ultrasonic insert; Group 3 - carbide bur + ultrasonic insert. Time spent on removal procedures, dental structure wear and amount of remaining cement agent were recorded and results submitted to ANOVA, Kruskal Wallis and Tukey-Kramer tests. RESULTS: Group 1 - 16'46", 33.33% and 6.99%; Group 2 - 12'31", 40% and 7.86%; and Group 3 - 10'24", 80% and 8.14%. Group 3 presented the most effective removal of glass fiber posts. CONCLUSION: There was no significant difference in efficiency among the evaluated techniques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".