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Record W2019576915 · doi:10.1212/wnl.56.10.1403

Triple “E” syndrome: Bilateral locked posterior fracture dislocation of the shoulders

2001· article· en· W2019576915 on OpenAlexaff
Muriel Brackstone, Stuart D. Patterson, Andrew Kertesz

Bibliographic record

VenueNeurology · 2001
Typearticle
Languageen
FieldMedicine
TopicTrauma Management and Diagnosis
Canadian institutionsWestern University
Fundersnot available
KeywordsPathognomonicShouldersMedicineElectrocutionEtiologySurgeryMedical emergencyInternal medicineDisease

Abstract

fetched live from OpenAlex

Bilateral locked posterior fracture dislocation of the shoulders is one of the least common injuries of the shoulder, and this injury has been suggested to be pathognomonic of seizures when diagnosed in the absence of trauma. The authors present a case of idiopathic bilateral locked posterior fracture dislocations of the shoulder, along with a review of the medical literature. The authors also present the "triple E syndrome," describing the possible etiologies of this injury: epilepsy (or any convulsive seizure), electrocution, or extreme trauma.

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)0.003
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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

Citations82
Published2001
Admission routes1
Has abstractyes

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