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Correlation of skeletal maturation stages determined by cervical vertebrae and hand-wrist evaluations.

2006· article· en· W1868853675 on OpenAlexaff
Carlos Flores‐Mir, Corr A. Burgess, Mitchell Champney, Robert J. Jensen, Micheal R. Pitcher, Paul W. Major

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntraclass correlationCervical vertebraeSpearman's rank correlation coefficientOrthodonticsWristMedicineRadiographyCorrelation coefficientBone ageAnatomyMathematicsSurgeryStatistics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.254
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations159
Published2006
Admission routes1
Has abstractyes

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