Dento‐alveolar measurements and histomorphometric parameters of maxillary and mandibular first molars, using micro‐CT
Bibliographic record
Abstract
BACKGROUND: Micro-CT is a high-resolution, non-invasive, and non-destructive imaging technique, currently acknowledged as a gold standard modality for assessing quantitatively and objectively dental morphology and bone microarchitecture parameters. PURPOSE: The aim of this study was to analyze critical dental and periodontal measurements characterizing the mandibular (MandFM) and maxillary (MaxFM) first molar architecture, as well as the corresponding bony socket, using micro-CT. MATERIALS AND METHODS: Thirty-eight human dried skulls (22-76 years) were scanned to enable the virtual analysis of 61 first molars. Depending on the type of measurement, the parameters were recorded on two-dimensional sections or directly on three-dimensional models. Tooth morphology was described by four aspects (e.g., tooth width, trunk length, root length, and root span), while the socket architecture was assessed by buccal plate thicknesses and bone density measurements. RESULTS: Minimum, maximum, and mean distances as well as cortical and trabecular bone densities were recorded in MandFM and MaxFM. It is noteworthy that the buccal plate thickness was found to be less than 1 mm in more than 55% of cases in MaxFM, whereas only in 20.8% of cases in MandFM (and even 0% at two sites). A wide range of bone densities was observed and the comparison between MandFM and MaxFM did not show a significant difference. Furthermore, cortical densities were negatively correlated with aging, while trabecular densities were not influenced. CONCLUSIONS: Using micro-CT, three-dimensional aspects of the human first molar morphology and microstructural parameters of the surrounding bone were evaluated in the mandible and in the maxilla. These comprehensive measurements and their correlation with aging may be of great importance for the use of immediate implant placement in molar extraction sockets and thus the potential long-term success of this treatment modality.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".