Reliability of different three-dimensional cephalometric landmarks in cone-beam computed tomography: A systematic review
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
OBJECTIVES: Conventional two-dimensional (2D) cephalometric radiography is an integral part of orthodontic patient diagnosis and treatment planning. One must be mindful of its limitations as it indeed is a 2D representation of a vaster three-dimensional (3D) object. Issues with projection errors, landmark identification, and measurement inaccuracies impose significant limitations, which may now be overcome with the advent of cone-beam computed tomography (CBCT). A systematic review of the reliability of different 3D cephalometric landmarks in CBCT imaging was conducted. MATERIALS AND METHODS: Electronic database searches were administered until October 2017 using PubMed, MEDLINE via OvidSP, EBMR and EMBASE via OvidSP, Scopus, and Web of Science. Google Scholar was used as an adjunctive search tool. RESULTS: Thirteen articles considering CBCT scans of human subjects from preexisting data sets were selected and reviewed. Most of the studies had methodological limitations and were of moderate quality. Because of their heterogeneity, key data from each could not be combined and were reported qualitatively. Overall, in 3D, midsagittal plane landmarks demonstrated greater reliability compared with bilateral landmarks. A minimum number of dental landmarks were reported, although most were recommended for use. CONCLUSIONS: Further research is required to evaluate the reliability of 3D cephalometric landmarks when evaluating 3D craniofacial complexes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it