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Record W7132593196

Tomographic evaluation of parallelism and asymmetry of rapid maxillary expansion with dental and skeletal anchorage

2024· book· es· W7132593196 on OpenAlexaboutno aff
Ana Lucia Ibarcena Llerena, Maria Alejandra Cacho Cruzado

Bibliographic record

VenueUniversidad Peruana Cayetano Heredia Institutional Repository · 2024
Typebook
Languagees
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsnot available
Fundersnot available
KeywordsAsymmetryGroup (periodic table)Parallelism (grammar)Maxilla
DOInot available

Abstract

fetched live from OpenAlex

Objetivo: Evaluar tomográficamente el paralelismo y asimetría de la expansión rápida del maxilar con anclaje dentario y esquelético. Metodología: Se emplearon 80 registros tomográficos, los cuales fueron divididos en 2 grupos: grupo con anclaje dentario y grupo con anclaje esquelético. Por cada grupo hubo 40 registros tomográficos, los cuales estuvieron constituidos por 20 registros pre expansión y 20 registros post expansión, de un ensayo clínico previo realizado en la Universidad de Alberta, Canadá. Las tomografías se reconstruyeron utilizando el software Xelis Dental. Para evaluar el paralelismo se calculó por medio de ratios a nivel de la región anterior (cavidad nasal) y posterior (foramen palatino) con lo que se determinó el porcentaje de expansión. Del mismo modo, para la asimetría se calcularon desviaciones estándar como referencia de corte para cavidad nasal, foramen palatino y cigomático. Resultados: No hubo diferencia significativa en el paralelismo entre los grupos de expansión. Asimismo, respecto a asimetría se encontró diferencia significativa (p<0.05) en cavidad nasal (CN) del grupo de expansión esquelética, presentando 27.5% de expansión asimétrica de la muestra. Conclusiones: Ninguno de los grupos de expansión presentaron paralelismo. Ambos grupos presentaron mayor cantidad de pacientes con expansión simétrica. El grupo con anclaje esquelético presentó mayor cantidad de pacientes con expansión asimétrica para cavidad nasal con diferencia significativa.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.245
Teacher spread0.231 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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