MétaCan
Menu
Back to cohort
Record W1821997855 · doi:10.2319/041315-242.1

Current trends in headgear use for the treatment of Class II malocclusions

2015· article· en· W1821997855 on OpenAlexaboutno aff
Eser Tüfekçi, Samuel B. Allen, Al M. Best, Steven J. Lindauer

Bibliographic record

VenueThe Angle Orthodontist · 2015
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsDentistryMedicineQuarter (Canadian coin)OrthodonticsFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate American and Canadian orthodontists' opinions and perceptions on the use of headgear in the treatment of Class II malocclusions. MATERIALS AND METHODS: An online survey was sent to randomly chosen orthodontists (n = 1000). RESULTS: The study was completed by 948 orthodontists; 62% of the orthodontists indicated that they were using headgear in their practice. Those who were not using the appliance (38%) reported that this was mainly due to the availability of better Class II correctors in the market and lack of patient compliance. Of those who use headgear, 24% indicated that the emphasis on headgear use during their residency was an influential aspect of their decision making (P < .05). Nearly a quarter of those who do not use headgear reported that learning about other Class II correctors through continuing education courses was an important factor (P < .05). There was no difference between the headgear users and nonusers in the year and location of practice. Compared with previous studies, this study showed a decline in the use of headgear among orthodontists. CONCLUSIONS: Despite a decline, more than half of the orthodontists (62%) believe headgear is a viable treatment. Availability of Class II correctors in the market and familiarity with these appliances though continuing education courses are the reasons for the remaining 38% of orthodontists to abandon use of the headgear.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.127
GPT teacher head0.366
Teacher spread0.239 · 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

Citations27
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueThe Angle OrthodontistSame topicOrthodontics and Dentofacial OrthopedicsFrench-language works237,207