Mandibular dental changes following serial and late extraction of mandibular second premolars
Bibliographic record
Abstract
OBJECTIVES: To determine changes in occlusal curves and dental tipping occurring from mandibular second premolar serial extraction, early extraction of deciduous mandibular second molars with missing second premolars, and late second premolar extraction compared with untreated controls. MATERIALS AND METHODS: Information was collected from 85 subjects at three time points: T0, prior to serial extraction; T1, after serial extraction and drift prior to orthodontic treatment, and pretreatment for the late premolar extraction patients; and T2, posttreatment. Untreated age- and gender-matched controls were used for comparison. Three occlusal curves were measured on digitized mandibular casts, and dental tipping was assessed using lateral cephalograms. RESULTS: At T0, there were no significant differences among groups. At T1, there was significant steepening of Monson's sphere and the curve of Wilson between early and late extraction and control groups. At T2, the differences in Monson's sphere and the curve of Wilson were fully corrected. At T1, there were significant differences in the tipping of mandibular 6's, 4's, and 3's between the early extraction groups compared with the late extraction and control groups. At T2, these differences in tipping were fully corrected. There were no differences in mandibular incisor tipping between groups at T1 or T2. CONCLUSIONS: Serial extraction produced steeper occlusal curves and significant tipping of mandibular first molars, first premolars, and canines after extraction and physiologic drift (T1). Accentuated occlusal curves and tooth tipping were fully corrected following orthodontic treatment (T2). Mandibular incisor position was unchanged by serial or late second premolar extraction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".