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Record W2962195777 · doi:10.1159/000501545

Periacetabular Osteotomy Performed with Imageless Computer-Assisted Navigation: Case Report

2019· article· en· W2962195777 on OpenAlexaff
Atul F. Kamath, Rachel Mays

Bibliographic record

VenueCase Reports in Orthopedic Research · 2019
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsIntellijoint Surgical (Canada)
Fundersnot available
KeywordsAcetabulumOrientation (vector space)Femoral headComputer-assisted surgeryHip dysplasiaDysplasiaComputer scienceSurgeryMedicineOrthodonticsPathologyRadiography

Abstract

fetched live from OpenAlex

Periacetabular osteotomy (PAO) is an effective surgical treatment for developmental hip dysplasia. The goal of PAO is to reorient the acetabulum to increase acetabular coverage of the femoral head, as well as to reduce contact pressures within the hip joint. The primary challenge of PAO is to accurately achieve the desired acetabular fragment orientation, while maximizing containment and congruency. As key parts of the procedure are performed out of direct field of view of the surgeon, combined with this challenge of precise spatial orientation, there is a potential role for technologies such as surgical navigation. Adjunctive technology may provide information on the orientation of repositioned acetabulum and may offer a useful assist in performing PAO. Here, we present a case of developmental dysplasia of the hip treated via PAO with the addition of an imageless computer navigation device. Surgery was successful, and, at 3 months after procedure, the patient was progressing well. To our best knowledge, this is the first case using imageless computer-assisted navigation in PAO surgery.

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)0.003
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.370
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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

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