A review of the experimental methods and results of testing the mechanical properties of Tunica Albuginea
Bibliographic record
Abstract
The present work provides a comprehensive review of the literature on the mechanical properties and existing human tunica albuginea tissue testing methods. Assessments were completed on papers reporting experimental values of Young's modulus, tensile strength, puncture strength, stiffness, toughness, and strain at the ultimate tensile strength (UTS). A high degree of variability in the reported experimental values was found; Young's modulus ranged from 5 MPa to 118 MPa, and tensile strength went from 1.1 MPa to 6.1 MPa. A comparison of the variability of the reported experimental values for puncture strength, stiffness, toughness, and strain at the UTS could not be completed due to a lack of experimental results. This review discusses the pathophysiology and surgical treatment of erectile dysfunction and Peyronie's disease, variability in the existing reported mechanical properties, the impact of the variability of mechanical properties on in silico models and explores the absence of a standardised testing method as a possible reason for the variable in results. Finally, this work attempts to provide suggestions for standardising future mechanical testing of the tunica albuginea through minimising and reporting freeze/thaw cycling, noting the proximal/distal region of the cadaver tunica sample, reporting the orientation (o'clock position) of the cadaver tunica sample, and testing the cadaver tunica samples in bi-axial tension. Ultimately, standardising the testing methodologies of the tunica albuginea will provide higher confidence in reported mechanical property values.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".