Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.083 | 0.036 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".