Bibliographic record
Abstract
The purpose of this study was to evaluate the microleakage of various root-end filling materials using a fluid filtration system. Sixty extracted human single-rooted teeth were used. The crowns were removed, the canals prepared, and root-end fillings placed. The samples were divided into two control and five experimental groups. The root-end filling materials tested were: amalgam, Intermediate Restorative Material (IRM), a dentin-bonded resin, Super-EBA, and mineral trioxide aggregate. The results showed that amalgam root-end fillings demonstrated significantly more microleakage than Super-EBA, dentin-bonded resin, or mineral trioxide aggregate. There was no significant difference between amalgam and IRM. However IRM was also not significantly different from the other three groups. There were no significant differences between the other three groups. The purpose of this study was to evaluate the microleakage of various root-end filling materials using a fluid filtration system. Sixty extracted human single-rooted teeth were used. The crowns were removed, the canals prepared, and root-end fillings placed. The samples were divided into two control and five experimental groups. The root-end filling materials tested were: amalgam, Intermediate Restorative Material (IRM), a dentin-bonded resin, Super-EBA, and mineral trioxide aggregate. The results showed that amalgam root-end fillings demonstrated significantly more microleakage than Super-EBA, dentin-bonded resin, or mineral trioxide aggregate. There was no significant difference between amalgam and IRM. However IRM was also not significantly different from the other three groups. There were no significant differences between the other three groups. ERRATUMJournal of EndodonticsVol. 27Issue 10PreviewIn the July 2001 Journal of Endodontics, a misprint appeared in Table 2 of “Microleakage of Root-End Filling Materials” by Howard M. Fogel and Marshall D. Peikoff (J Endodon 2001;27:456–8). The corrected table appears below. We regret the error and any resultant confusion. Full-Text PDF
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".