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Record W4211253421 · doi:10.1002/9780471740360.ebs1204

Tissue Mechanics

2006· other· en· W4211253421 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWiley Encyclopedia of Biomedical Engineering · 2006
Typeother
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsViscoelasticityElastinHyperelastic materialMaterials scienceBiomedical engineeringMechanicsAnatomyComposite materialStructural engineeringEngineeringFinite element methodPhysicsPathology

Abstract

fetched live from OpenAlex

Abstract Tissue mechanics is the field of endeavour that seeks to understand and describe the links between structure and mechanical function in the soft and hard tissues of the human body. Much of the research work has been done in the connective tissues of the body (e.g., bone, tendons, cartilage, arteries, and skin) where mechanical demands are greatest; however, all tissues have mechanical features of interest. Approaches to the field have included: (1) use of structural anatomy as a means to understanding natural design, (2) mechanical engineering analysis of structures based on continuum mechanics, and (3) materials science study of detailed links between structure and function. As natural tissues are all composite materials, understanding of their mechanical function demands study of the mechanical properties and architectural arrangement of the individual structural components, particularly: strong, stiff collagen fibers; the physiological rubber elastin; hydroxyapatite mineral; and proteoglycan sol/gels. The mechanical features of tissues include marked anisotropy, nonlinear stress‐strain relations, viscoelasticity, preconditioning behavior, and the presence of pre‐stress. Most studies of the mechanical behavior of tissues have been carried out in the laboratory, with samples removed from cadavers or animals, cut or machined to shape, and tested either fresh or after storage. Commercial testing machines based on electromechanical or hydraulic systems are widely used, as are custom‐built apparatus. Testing is also carried out in living animals or patients. In either case, determination of sample geometry or deformations are difficult. Mathematical description of data is an important part of tissue mechanics, as is modeling of 3‐dimensional stress‐strain behavior. Soft tissues require the use of large deformation (finite) elasticity equations. Modeling may either be phenomenological (seeking to describe behavior using model systems that do not reference structure) or may be explicitly based on knowledge of tissue architecture. Phenomenological models have often been based on linear or quasilinear viscoelastic theory derived from previous work on polymer materials. Constitutive equations, particularly those based on development of strain energy density functions, have been widely used as a means to describing tissue behavior under arbitrary loading. In a complementary development, finite element analysis has found wide use for analysis of complex structures. Tissue mechanics is a tool both for: (1) the study of natural structures in health and disease, and (2) technological application, which, in recent years, has included design of surgical replacements and surgical technique, evaluation and design of tissue engineered replacements, and analysis/prevention of injuries caused by automobile accidents, blasts, and other 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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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