Synchrotron-radiation-based X-ray micro-computed tomography reveals dental bur debris under dental composite restorations
Bibliographic record
Abstract
Dental burs are used extensively in dentistry to mechanically prepare tooth structures for restorations (fillings), yet little has been reported on the bur debris left behind in the teeth, and whether it poses potential health risks to patients. Here it is aimed to image dental bur debris under dental fillings, and allude to the potential health hazards that can be caused by this debris when left in direct contact with the biological surroundings, specifically when the debris is made of a non-biocompatible material. Non-destructive micro-computed tomography using the BioMedical Imaging & Therapy facility 05ID-2 beamline at the Canadian Light Source was pursued at 50 keV and at a pixel size of 4 µm to image dental bur fragments under a composite resin dental filling. The bur's cutting edges that produced the fragment were also chemically analyzed. The technique revealed dental bur fragments of different sizes in different locations on the floor of the prepared surface of the teeth and under the filling, which places them in direct contact with the dentinal tubules and the dentinal fluid circulating within them. Dispersive X-ray spectroscopy elemental analysis of the dental bur edges revealed that the fragments are made of tungsten carbide-cobalt, which is bio-incompatible.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".