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The Lax Shoulder in Females

2000· article· en· W4312861508 on OpenAlexaff
Greg A. Brown, Jee Lim Tan, Alexandra Kirkley

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2000
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsFowler Kennedy Sport Medicine Clinic
Fundersnot available
KeywordsMedicineShouldersContext (archaeology)Ligamentous laxityShoulder jointJoint instabilitySurgeryPhysical therapy

Abstract

fetched live from OpenAlex

A review of the existing data on shoulder laxity in females reveals there are insufficient data to confirm the commonly held belief that shoulders in females are more lax than shoulders in males. Laxity is not synonymous with instability. Although females may have increased generalized joint laxity relative to males, generalized joint laxity does not correlate with shoulder laxity. There is conflicting data regarding shoulder laxity and gender. A review of patients with multidirectional instability who were treated operatively showed that 55% of the patients were female (N = 94) and 45% were male (N = 77), but the number or gender of patients who were treated nonoperatively was not reported. Multidirectional instability is reviewed in the context of the lax shoulder in the female. Initial treatment should be nonoperative, emphasizing physical therapy and dynamic stabilization of the shoulder. If nonoperative treatment fails, open or arthroscopic inferior capsular shift stabilization is recommended. Additional basic science and clinical trials are needed to determine whether thermal capsulorrhaphy should be considered in the treatment of patients with multidirectional instability of the shoulder.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.180
GPT teacher head0.503
Teacher spread0.323 · 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 designObservational
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

Citations49
Published2000
Admission routes1
Has abstractyes

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