Gas permeability: a new quantitative method to assess endodontic leakage
Bibliographic record
Abstract
AIM: The aim of this study was to evaluate a new endodontic leakage measurement method. MATERIALS AND METHODS: Permeability was assessed measuring the gas flow passing through the root. Positive and negative tests were carried out to assess the validity of the method. We used glass capillaries for calibration (diameters of 15, 30, 40, 50 and 75 microm). The applicability of the method was assessed with human teeth using three sealing methods: GuttaFlow (GF) and a single cone; Pulp Canal Sealer (PCS) and a single cone; PCS and system B. RESULTS: This method demonstrated to be highly reproducible as the standard deviation was approximately 1% on average with glass capillaries. Significantly higher leakage (p<0.05) was recorded for endodontic treatment with GF and single cone compared to PCS and single cone and PCS with system B. CONCLUSION: Gas permeability is quantitative, sensitive, non-destructive and reproducible and seems appropriate for endodontic tests. It would participate in the indirect comprehension of leakage phenomena.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".