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Record W4397022788 · doi:10.7759/cureus.60507

Bilateral Sternalis Muscles: The Clinical Significance of This Rare Discovery

2024· article· en· W4397022788 on OpenAlexaff
Annie Shi Ru Li, Michelle Sue, Peter Lombardi, Harun S Bola, Danielle C. Bentley

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldMedicine
TopicPectus Deformity Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineCadaveric spasmAnatomyDissection (medical)Clinical significancePresentation (obstetrics)Pectoralis major muscleRadiologyPathology

Abstract

fetched live from OpenAlex

This case report explores the physical characteristics and clinical significance of the sternalis muscle, an uncommon anatomical variation of the anterior thoracic wall. If present, the sternalis muscle may distort diagnostic images and can be associated with incorrect interpretation of such medical images, misdiagnoses, and even surgical complications. As such, enhancing clinicians' knowledge of this muscle and improving its recognition is of the utmost importance. In this case report, a rare bilateral sternalis muscle that was discovered during an educational human cadaveric dissection of a 73-year-old Black male is described. The right sternalis muscle fibres extended from the mid-sternal level to the right sternocostal arch, measuring 11.5 cm in length and 3.4 cm at its largest width. In contrast, the smaller left sternalis muscle fibres measured only 5.6 cm in length and 1.2 cm at its greatest width. This rare bilateral presentation of the sternalis muscle is documented in approximately one-third of all reported sternalis cases with an associated estimated prevalence as low as 1.7% among the general population. Serving as a reminder of the intricate anatomical complexities that continue to challenge and intrigue medical professionals, this report advocates for continued education of anatomical variations to enhance patient care and medical practices.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.360
Teacher spread0.307 · 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 teacher head, 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

Citations3
Published2024
Admission routes1
Has abstractyes

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