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Record W4297322448 · doi:10.1016/j.ijscr.2022.107711

Acute combined collateral ligaments injury of the elbow without any fracture or dislocation-a case report

2022· article· en· W4297322448 on OpenAlexaff
Marouane Bouloudhnine, Mohamed Hamdi Elgawadi

Bibliographic record

VenueInternational Journal of Surgery Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicElbow and Forearm Trauma Treatment
Canadian institutionsHand and Upper Limb Clinic
Fundersnot available
KeywordsMedicineElbowLigamentMedial collateral ligamentCollateralSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: The combination of both collateral ligaments injury in the elbow without fractures or dislocations is not reported in the literature. CASE PRESENTATION: a case report of rare acute combined collateral ligaments injury of the elbow was treated surgically by repairing both collateral ligament complexes with two different approaches. CLINICAL DISCUSSION: Clinical examination at 3 months showed a stable elbow with a flexion arc from 0 to 140. 10 degrees residual varus laxity was observed. Pronation and supination were unrestricted. The patient experienced mild pain and was able to do push up and was completely satisfied with the result. CONCLUSION: The case presented is the first case presented in the literature with acute combined and isolated collateral ligaments injury of the elbow. Based on the clinical result obtained. We propose acute surgical approach of both collateral ligaments for such types of injury.

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)0.004
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 score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0030.004
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.320
Teacher spread0.294 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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