Correlation of skeletal maturation stages determined by cervical vertebrae and hand-wrist evaluations.
Bibliographic record
Abstract
The aim of this study was to assess the correlation between the Fishman maturation prediction method (FMP) and the cervical vertebral maturation (CVM) method for skeletal maturation stage determination. Hand-wrist and lateral cephalograms from 79 subjects (52 females and 27 males) were used. Hand-wrist radiographs were analyzed using the FMP to determine skeletal maturation level (advanced, average, or delayed) and stage (relative position of the individual in the pubertal growth curve). Cervical vertebrae (C2, C3, and C4) outlines obtained from lateral cephalograms were analyzed using the CVM to determine skeletal maturation stage. Intraexaminer reliability (Intraclass correlation coefficient [ICC]) for both methods was calculated from 10 triplicate hand-wrist and lateral cephalograms from the same patients. An ICC coefficient of 0.985 for FMP and an ICC of 0.889 for CVM were obtained. A Spearman correlation value of 0.72 (P < .001) was found between the skeletal maturation stages of both methods. When the sample was subgrouped according to skeletal maturation level, the following correlation values were found: for early mature adolescents 0.73, for average mature adolescents 0.70, and for late mature adolescents 0.87. All these correlation values were statistically different from zero (P < .024). Correlation values between both skeletal maturation methods were moderately high. This may be high enough to use either of the methods indistinctively for research purposes but not for the assessment of individual patients. Skeletal level influences the correlation values and, therefore, it should be considered whenever possible.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".