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Record W2007142245 · doi:10.1097/bth.0b013e31822911fd

Rehabilitation Considerations in the Management of Terrible Triad Injury to the Elbow

2011· review· en· W2007142245 on OpenAlexaff
Joey G. Pipicelli, Shrikant J. Chinchalkar, Ruby Grewal, George S. Athwal

Bibliographic record

VenueTechniques in Hand and Upper Extremity Surgery · 2011
Typereview
Languageen
FieldMedicine
TopicElbow and Forearm Trauma Treatment
Canadian institutionsWestern UniversitySt Joseph's Health CareHand and Upper Limb Clinic
Fundersnot available
KeywordsMedicineElbowTriad (sociology)RehabilitationPhysical medicine and rehabilitationRadial headBiomechanicsIntervention (counseling)Radial head fracturePhysical therapySurgeryAnatomyNursingPsychoanalysis

Abstract

fetched live from OpenAlex

An elbow dislocation associated with a radial head and coronoid fractures is termed a terrible triad. This injury almost always renders the elbow unstable requiring surgical intervention. The primary goal of surgery is to stabilize the elbow to permit early motion to prevent stiffness. Recent literature has improved our understanding of elbow anatomy and biomechanics as well as the pathoanatomy of this injury. This article reviews key concepts that will allow the surgeon and therapist to apply an systematic rehabilitation approach when managing such injuries.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.083
GPT teacher head0.357
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2011
Admission routes1
Has abstractyes

Explore more

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