Design and validation of an automated dual‐arm instrumented intravaginal dynamometer
Bibliographic record
Abstract
AIMS: (1) To present the design of a novel intravaginal dynamometer (IVD) capable of measuring vaginal closure force on both the anterior and posterior arms, (2) to use bench testing to validate the force, speed of arm opening, and positional accuracy of load measurement along the IVD arms, and (3) to present in vivo force measurements made with this device, comparing forces measured by the anterior and posterior arms. METHODS: IVD load measurements were validated against an Instron® Universal Tester, arm opening speeds were validated using video analysis, and position-load accuracy was validated against calibration weights. In vivo IVD data were acquired from female volunteers during passive opening and pelvic floor muscle contraction tasks. Anterior and posterior IVD arm force outcomes were compared. RESULTS: Forces measured by the IVD and Instron® exhibited a strong linear relationship with excellent model fit. The speed control system was valid when tested under physiological loading conditions, however smaller antero-posterior opening diameters (25 and 30 mm) exhibited some error. The loading position along the IVD arms had no effect on force outcomes. In vivo data exhibited differences between force outcomes measured at the anterior and posterior aspects of the vagina during active contraction and passive elongation of the pelvic floor muscles. CONCLUSIONS: This IVD design demonstrates valid load measurement and speed control during bench testing. Active and passive forces measured are consistent with the literature. With dual instrumented arms, this device allows for further investigation into the source of measured vaginal closure forces.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".