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Implant vs screw loading protocols in orthodontics.

2006· article· en· W2116771327 on OpenAlexaff
Elizabeth Ohashi, Óscar E. Pecho, Milagros Moron, Manuel O. Lagravère

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMEDLINEMedicineChecklistDentistryOrthodonticsWeb of scienceEvidence-based dentistryAlternative medicineMeta-analysisPsychologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: This systematic review presents the loading protocols applied when using implants and/or screws in orthodontic treatments. MATERIALS AND METHODS: Clinical trials which assessed the use of implants and/or screws for orthodontic anchorage and studies involving treatment on syndromic patients, surgery, other simultaneous treatments, or appliances (ie mini-plates) were considered. Electronic databases (Medline, Medline In-Process & Other Non-Indexed Citations, Lilacs, Pubmed, Embase, Web of Science, and All Evidence Based Medicine Reviews) were searched with the help of a senior Health Sciences librarian. Abstracts which appeared to fulfill the selection criteria were selected by consensus. The original articles were then retrieved and evaluated with a methodological checklist. References were also hand searched for possible missing articles. RESULTS: Eleven articles fulfilled the selection criteria established. Five studies involved the use of implants while six involved the use of screws for orthodontic purposes. An individual methodological analysis for each article was made. CONCLUSIONS: Loading protocols for implants involve a minimum waiting period of 2 months before applying orthodontic forces while loading protocols for screws involve immediate loading or a waiting period of 2 weeks to apply forces. Success rates for implants were on average higher than for screws.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.282
Teacher spread0.246 · 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

Citations59
Published2006
Admission routes1
Has abstractyes

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