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Record W2148798532 · doi:10.1177/1460408610367967

Soft-tissue ankle injuries

2010· article· en· W2148798532 on OpenAlexaboutno aff
GS Matharu, PS Najran, KM Porter

Bibliographic record

VenueTrauma · 2010
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnkleSoft tissueLigamentPresentation (obstetrics)Soft tissue injuryPhysical examinationSurgeryAnkle injuryEmergency departmentAcute injury

Abstract

fetched live from OpenAlex

Soft-tissue ankle injuries are extremely common and frequently present in the emergency department or to the general practitioner. The lateral ligament complex is most commonly affected, usually following an injury with the ankle in an inverted, plantar-flexed position. The diagnosis is usually clinical, and delayed examination and reassessment 3—5 days after injury is recommended as pain and swelling hinder accurate assessment immediately following injury. Applying the Ottawa ankle rules can reduce the number of unnecessary radiographs. Treatment is usually non-operative with the focus on controlling ankle swelling and pain, and early restoration of ankle movements. Surgical repair of ligaments may be indicated in certain cases, though the role of surgery in the acute setting remains unclear. In the present review, we discuss the anatomy, mechanism of injury, risk factors, clinical presentation, diagnosis, treatment and outcome of soft-tissue ankle injuries as well as consider how such injuries may be prevented.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.018
GPT teacher head0.289
Teacher spread0.270 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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