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Record W4393347285 · doi:10.1177/2050313x241241191

Magneto-dynamic tool for full arch immediate loading in post-traumatic restoration with narrow implants: A case report

2024· article· en· W4393347285 on OpenAlexaboutno aff
Gabriele Cervino, Luca Fiorillo, Nicola Scotti, Francesco Alessandro Motta, Francesco Maria Motta, Jacopo Colombo, Artak Heboyan, Domenico Baldi

Bibliographic record

VenueSAGE Open Medical Case Reports · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsDenturesMedicineDentistryArchOrthodonticsRehabilitationDental prosthesisDental archImplantSurgery

Abstract

fetched live from OpenAlex

New surgical techniques using narrow, tilted implants positioned through a magneto-dynamic tool in guided surgery for a Toronto restoration. A 69-year-old woman wanted fixed rehabilitation to replace her removable complete dentures. A cone-beam computed tomography showed significant bone resorption in both the maxillary and mandibular regions. The plan was to load the entire upper arch with six implants immediately, while removable partial dentures were recommended for the lower jaw. The guided surgery project was aligned with the new dentures, and the laboratory created a printed cast with dental implant analogues in planned positions. A metal-reinforced denture was constructed, and surgery was performed to place six narrow implants using the magneto-dynamic instrument. The denture was directly screwed onto multi-unit abutments. Final rehabilitation was completed after 6 months. Narrow implants can be a good option for fixed, full-arch rehabilitations. Further research is needed to confirm these findings on a larger scale.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0110.005
Insufficient payload (model declined to judge)0.0030.002

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 head0.023
GPT teacher head0.354
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations5
Published2024
Admission routes1
Has abstractyes

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