Relationship between positive clinical VTO and post-treatment soft tissue profile following phase l growth modification therapy
Bibliographic record
Abstract
Introduction: Facial profile improvement is goal of cotemporary orthodontics and a reason to seek orthodontic therapy. The soft tissue profile plays a important role on orthodontic diagnosis and treatment planning. The objective of this study is to investigate the relationship between positive clinical VTO and actual post-treatment soft tissue profile after phase l therapy of growth modification in Class II. Materials & Method: Pretreatment simulation of post-treatment and actual post-treatment profile photographs of 30 class ll div l patients treated with twin block appliance were compared. Three profile photographs of each subject; pretreatment, positive clinical VTO and post-treatment were taken and on each photograph four angles; Nasofacial (NF), Nasomental (NM), Mentocervical (MC) and Nasolabial (NL) were drawn and measured. Mean, standard deviation, success and coefficient of determination of each angle was measured and linear regressions analysis was applied to find out the correlation. Result: Nasolabial and nasomental angles showed greater success i.e. 81.4% and 68.1% respectively showing greater correlation, while nasofacial and mentocervical angles showed less success i.e. 48.1% and 48.3% respectively showing less correlation. Linear regression analysis revealed that positive clinical VTO significantly predicted post-treatment profile whereas coefficient of determination for nasomental and mentocervical angles was 76.5% and 60% representing a better goodness of fit while nasolabial and nasofacial angles was 53.6% and 51.6% demonstrating poor fit of regression lines. Conclusion: Even though there is improved facial profile obtained by protracting the mandible into class l relation in a chair side maneuver in class ll div l malocclusions, yet the orthodontist should be tentative when predicting the outcome of growth modification to get benefit of this therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".