Assessment of smear layer removal protocols in curved root canals
Bibliographic record
Abstract
This study sought to assess if the final rinse protocol interferes with the smear layer removal in the apical area of curved canals. Sixty-four extracted human mandibular molars with curved mesial roots were instrumented with rotary files and divided into six experimental groups for final rinse: 1EDTA (syringe irrigation with 1 mL of 17% ethylenediaminetetraacetic acid (EDTA) ), 5EDTA (syringe irrigation with 5 mL of 17% EDTA), 1EDTA-P (syringe irrigation with 1 mL of 17% EDTA + pumping with gutta-percha point), 5EDTA-P (syringe irrigation with 5 mL of 17% EDTA + pumping with gutta-percha point), 1EDTA-EA (syringe irrigation with 1 mL of 17% EDTA + EndoActivator) and 5EDTA-EA (syringe irrigation with 5 mL of 17% EDTA + EndoActivator). Final rinsing was carried out over 3 min. The specimens were split lengthwise and observed under a scanning electron microscope using a score criterion. Comparison among the groups showed statistically significant difference only between the 5EDTA-EA group and the other groups (Kruskal-Wallis and Dunn's post-hoc tests, P < 0.05). The combination of 5 mL of 17% EDTA and 3 mL of 2.5% sodium hypochlorite (NaOCl) with the EndoActivator removed smear layer from the apical area of curved root canals more effectively than the other protocols used.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".