Intra‐arch dimensional measurement validity of laser‐scanned digital dental models compared with the original plaster models: a systematic review
Bibliographic record
Abstract
A systematic review was undertaken to evaluate the validity of intra-arch dimensional measurements made from laser-scanned digital dental models in comparison with measurements directly obtained from the original plaster casts (gold standard). Finally included articles were only those reporting studies that compared measurements from digital models produced from laser scanning against their plaster models. Measurements from the original plaster models should have been made using a manual or digital caliper (gold standard). Articles that used scans from impressions or digital photographs were discarded. Detailed individual search strategies for Cochrane, EMBASE, MEDLINE, PubMed, and LILACS were developed. The references cited in the selected articles were also checked for any references that could have been missed in the electronic database searches. A partial gray literature search was undertaken using Google Scholar. The methodology of selected studies was evaluated using the 14-item quality assessment tool for diagnostic accuracy studies (QUADAS). Only 16 studies were finally included for the qualitative/quantitative synthesis. The selected studies consistently agree that the validity of measurements obtained after using a laser scanner from plaster models is similar to direct measurements. Any stated differences would be unlikely clinically relevant. There is consistent scientific evidence to support the validity of measurements from digital dental models in comparison with intra-arch dimensional measurements directly obtained from them.
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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 | 0.018 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".