Changes in mandibular incisor position and arch form resulting from Invisalign correction of the crowded dentition treated nonextraction
Bibliographic record
Abstract
OBJECTIVE: To investigate changes in mandibular incisor position resulting from Invisalign correction of the crowded dentition without extraction. MATERIALS AND METHODS: A retrospective chart review was completed on 61 adult White patients. Patients were categorized into three groups based on the value of pretreatment crowding of the lower dentition: 20 mild (2.0-3.9 mm), 22 moderate (4.0-5.9 mm), and 19 severe (>6.0 mm). Cephalometric radiographs were measured to determine lower incisor changes. Interproximal reduction and changes in arch width were also measured. Statistical evaluation of T0 and T1 values using paired t-tests and analysis of covariance were applied to evaluate mean value changes. RESULTS: Lower incisor position and angulation changes were statistically significant in the severe crowding group. There were no statistically significant differences in lower incisor position between the mild and moderate crowding groups. There was a statistically significant increase in buccal expansion in each of the three groups. CONCLUSIONS: Invisalign(®) treatment can successfully resolve mandibular arch crowding using a combination of buccal arch expansion, interproximal reduction, and lower incisor proclination. When there is <6 mm of crowding, lower incisor position remained relatively stable. The lower incisors proclined and protruded in the more severely crowded dentitions (>6 mm).
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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 | 0.001 |
| 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) | 0.001 | 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".