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Record W2008083907 · doi:10.1155/2013/432675

The Retroacetabular Angle Determines the Safe Angle for Screw Placement in Posterior Acetabular Fracture Fixation

2013· article· en· W2008083907 on OpenAlexaff
Ayman M.A. Tadros, Thomas R. Oxland, Peter J. O’Brien

Bibliographic record

VenueISRN Orthopedics · 2013
Typearticle
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInclination angleTangentOrthodonticsArticular surfaceComputed tomographyFixation (population genetics)MedicineMathematicsPopulationNuclear medicineGeometrySurgery

Abstract

fetched live from OpenAlex

Introduction. A method for the determination of safe angles for screws placed in the posterior acetabular wall based on preoperative computed tomography (CT) is described. It defines a retroacetabular angle and determines its variation in the population. Methods. The retroacetabular angle is the angle between the retroacetabular surface and the tangent to the posterior acetabular articular surface. Screws placed through the marginal posterior wall at an angle equal to the retroacetabular angle are extraarticular. Medial screws can be placed at larger angles whose difference from the retroacetabular angle is defined as the allowance angles. CT scans of all patients with acetabular fractures treated in our institute between September 2002 to July 2007 were used to measure the retroacetabular angle and tangent. Results. Two hundred thirty one patients were included. The average (range) age was 42 (15-74) years. The average (range) retroacetabular angle was 39 (30-47) degrees. The average (range) retroacetabular tangent was 36 (30-45) mm. Conclusions. Placing the screws at an average (range) angle of 39 (33-47) degrees of anterior inclination with the retroacetabular surface makes them extraarticular. Angles for medial screws are larger. Safe angles can be calculated preoperatively with a computer program.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.609

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 head0.013
GPT teacher head0.268
Teacher spread0.255 · 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 designNot applicable
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
Published2013
Admission routes1
Has abstractyes

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