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Record W4416596589 · doi:10.1002/ca.70047

Fascia, Eh. What Is It? What Is It Good for?

2025· article· en· W4416596589 on OpenAlexaff
Paul E. Neumann, Heba Labib, Martin Lhuaire, Noel T. Boaz, Geoffroy Noël, Carlos A. Suárez‐Quian, Chernet Bahru Tessema, Peter J. Ward, Anthony J. Weinhaus, Mahindra K. Anand, Alan J. Detton

Bibliographic record

VenueClinical Anatomy · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsMcGill UniversityDalhousie University
Fundersnot available
KeywordsFasciaPerspective (graphical)Connective tissuePosition (finance)Deep fasciaMeaning (existential)

Abstract

fetched live from OpenAlex

Opinions on the meaning of the term fascia appear to have been diverging for the past quarter century. In 1998, the definition of fascia in the international standard anatomical nomenclature was narrowed by removing the term fascia superficialis. On the other hand, fascia researchers, who continue to widely accept the term superficial fascia, have progressively broadened their definition of fascia and proposed that fasciae constitute an anatomical system, the fascial system. Here we examine competing concepts from an anatomical perspective with the goal of finding a position that could lead to a consensus among anatomists, other biomedical scientists and health practitioners with an interest in fascia. We endorse a return to the traditional view that fasciae are fibrous membranes that compartmentalize and connect parts of the body, that they are primarily composed of sheets or sheaths of dense irregular connective tissue, and that they are not parts of well-defined organs. They are prominent components of the integument, musculature, lining of the body cavities, and extraperitoneal spaces. The proposal that fibrous membranous components of the skeleton and nervous system are also fasciae merits further study and discussion.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.036
GPT teacher head0.398
Teacher spread0.362 · 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 designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

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