Physical properties and hydration behavior of a fast-setting bioceramic endodontic material
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: To investigate the physical properties and the hydration behaviour of the fast-setting bioceramic iRoot FS Fast Set Root Repair Material (iRoot FS) and three other endodontic cements. METHODS: iRoot FS, Endosequence Root Repair Material Putty (ERRM Putty), gray and white mineral trioxide aggregate (G-MTA & W-MTA), and intermediate restorative material (IRM) were evaluated. The setting time was measured using ANSI/ADA standards. Microhardness was evaluated using the Vickers indentation test. Compressive strength and porosity were investigated at 7 and 28 days. Differential scanning calorimetry (DSC) was employed for the hydration test. RESULTS: iRoot FS had the shortest setting time of the four bioceramic cements (p < .001). The microhardness values of iRoot FS, ERRM Putty and MTA increased at different rates over the 28 days period. At day one, ERRM Putty had the lowest microhardness of the bioceramic cements (p < .001), but reached the same level as MTA at 4, 7 and 28 days. The microhardness of iRoot FS was lower than that of W-MTA at 7 and 28 days (p < .05). The porosity of the materials did not change after 7 days (p < .05). The compressive strength values at 28 days were significantly greater for all bioceramic groups compared to those at 7 days (p < .01). ERRM Putty had the highest compressive strength and the lowest porosity of the evaluated bioceramic cements (p < .05), followed by iRoot FS, W-MTA, and G-MTA, respectively. DSC showed that iRoot FS hydrated fastest, inducing an intense exothermic reaction. The ERRM Putty did not demonstrate a clear exothermic peak during the isothermal calorimetry test. CONCLUSIONS: iRoot FS had a faster setting time and hydrating process than the other bioceramic cements tested. The mechanical properties of iRoot FS, G-MTA and W-MTA were relatively similar.
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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) | 0.000 | 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) | 0.000 | 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 it