Possible Approaches in Modelling Rearrangement in a Microstructured Material
Bibliographic record
Abstract
Biological materials can be regarded as composites with spheroidal and fibre-like inclusions, representing cells and collagen fibres, respectively. The orientation and arrangement of the inclusions in a biological tissue is crucial to the determination of the mechanical properties of the material. Furthermore, the reorientation and rearrangement of the inclusions due to the deformation and external forces is of primary interest when dealing with growth and remodelling. We propose to look at the presence of inclusions as a source of internal hyperstaticity: when the material undergoes deformation, a generic inclusion is drifted by the deformation, but at the same time it “feels” the stress field and tends to carry a portion of stress proportional to its stiffness relative to that of the surrounding matrix. With this assumption, we can extend the classical “drift” evolution law for the unit vector field, in order to take the hyperstaticity into account. This method might be used in the description of remodelling in disordered media, such as biological tissues, and may be extended to investigate the reorientation of preferred directions of micro-structural elements in media described with a continuum approach.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".