Comparative Evaluation on the Fracture Resistance of Endodontically Treated Teeth Restored with three different Post : Pre-fabricated Carbon Fiber Posts, Customized Glass Fiber Posts, and SFRC-Relined Fiber Posts- A Research Protocol. (Preprint)
Bibliographic record
Abstract
Background: Endodontically treated teeth are prone to fractures due to the loss of tooth structure, caries removal, access cavity preparation, and scaling, resulting in compromised strength in the teeth. Posts are used for restoring teeth that have undergone this process, but the role of different fiber posts in resisting fractures in teeth is unclear. Customized carbon fiber posts, customized glass fiber posts, and fiber posts relined with short fiber-reinforced composite (SFRC) are biomechanically efficient. SFRC is used as a relining material around the fiber post to improve adaptation to the root canal. Objective: This study aims to evaluate and compare the fracture resistance of endodontically treated teeth restored with prefabricated carbon fiber posts, customized glass fiber posts, and SFRC-relined fiber posts. Methods: In the current in vitro experimental study, the post specimens will be tested on 30 extracted single-rooted human teeth. These will be similar in size. The specimens will go through endodontic treatment and preparation for the post space, after which they will be randomly assigned to groups based on the type of post system: prefabricated carbon fiber posts, customized glass fiber posts, or SFRC-relined fiber posts. These will be cemented using a dual-cured resin cement. The specimens will then be restored using a standardized core build-up and tested for fracture resistance using a universal testing machine. A compressive load will be applied to each specimen at a constant crosshead speed of 1 mm/min until fracture of the specimen occurs. The maximum load at failure will be recorded in newtons. Statistical analysis will be conducted using a 1-way ANOVA. Results: Institutional ethics approval was granted by the Institutional Ethics Committee of Datta Meghe Institute of Higher Education and Research in January 2025 (DMIHER[DU]/IEC/2025/543). Sample collection and specimen preparation are scheduled to begin in February 2026, with mechanical testing expected to be completed by April 2026. As of April 2025, no specimens had been tested, and data analysis had not commenced. This is a nonfunded in vitro study, and data analysis is anticipated to be completed by May 2026. The results are expected to be submitted for publication by mid-2026. Conclusions: This study is expected to generate comparative biomechanical evidence on the fracture resistance of different fiber-based post systems, potentially aiding clinicians in selecting optimal restorative strategies for endodontically treated teeth.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".