Determining the Diffusion Coefficient for Articular Cartilage Modelled As Homogeneous and Porous Material
Bibliographic record
Abstract
Porous materials are defined as materials consisting of a 'matrix' in which the voids are filled with gas or liquid.Porous materials also include biological tissues, because they consist of dispersed cells isolated by voids (pores) through which nutrients flow to all cells in them.An example of such tissue is articular cartilage, in which the size of the pores is estimated to be between 2 nm and 6 nm.The study involved determining the diffusion coefficient value for a selected tissue (articular cartilage) during cooling, assuming a model for homogeneous and porous material.The results obtained confirm that the applied material model impacts on the values of the diffusion coefficient.Higher coefficient values were obtained for the model taking into account the porosity of the sample than for the homogeneous material model.In addition, a decrease in temperature causes a decrease in the diffusion coefficient value.The results obtained can be used in the future to analyse the behaviour of a biological sample during the cryopreservation process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".