Ca(<scp>OH</scp>)<sub>2</sub> application modes: <i>in vitro</i> alkalinity and clinical effect on bacteria
Bibliographic record
Abstract
AIM: To compare five calcium hydroxide (CH) products, CH-gutta-percha Plus points(®) (CHGP) and conventional CH paste, for their ability to maintain alkalinity and to assess the clinical antimicrobial effect of CHGP. METHODOLOGY: Calcium hydroxide products were tested in the presence of standardized dentine powder or by titrating them with 1 mol HCl, expressed in mL (±SD). In a clinical trial, 21 single-rooted teeth with primary apical periodontitis were medicated with CHGP or with conventional CH paste. Bacterial samples were taken before and after chemo-mechanical preparation, after dressing and after leaving canals empty but sealed. To compare groups, anova with Tukey's test was used in the laboratory study and Fisher's exact test in the clinical study. Significance level was set at 5%. RESULTS: Pure CH with water (8.5 ± 0.1) and Calasept (9.3 ± 0.1) maintained the highest alkalinity, followed by the gel-like products DS CaOH gel (7.3 ± 0.3) and Ultracal XS (6.8 ± 0.2) and then Biokalkki (6.3 ± 0.3) and Calxyl blue (5.1 ± 0.2). All CH paste products had higher values compared with CHGP (1.6 ± 0.1) (P < 0.05). Saturated solutions of the products were all neutralized to pH 8.6 within 24 h by dentine powder addition. Clinically, culture-negative results were obtained in 5/10 canals in the CHGP group and 7/11 with conventional CH (P > 0.05). CONCLUSIONS: Aqueous CH mixtures kept high pH better than viscous gel products or CHGP. Dentine powder had equal buffering effect on each product tested. CHGP and traditional CH paste both had an antimicrobial effect in the clinical setting, but there was no significant difference between the groups.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".