Influence of cortical canal architecture on lacunocanalicular pore pressure and fluid flow
Bibliographic record
Abstract
Bone is a dynamic tissue that undergoes structural modification in response to its mechanical environment, but how bone cells sense and respond to loading conditions remains incompletely understood. Current theories focus on strain-induced fluid flow for the primary means of mechanotransduction. To examine the influence of age-related cortical rarefaction on lacunocanalicular fluid characteristics, coupled fluid flow and mechanical computational models of bone specimens representing young, mid-age and aged samples were derived artificially from the same original micro-computed tomography image data. Simulated mechanical loading was applied to the bone models to induce pressure-driven interstitial fluid flow. Results demonstrated a decrease in pore pressure and fluid velocity magnitudes with age as a result of increased cortical porosity. Mean canal separation, as opposed to canal size, was implicated as a primary factor affecting age-related fluid dynamics. Future investigations through refinement of the model may implicate fluid stasis or inadequate nutrient transport experienced by osteocytes as a key factor in the initiation of cortical remodelling events.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".