Instrument for determining the complex shear modulus of soft-tissue-like materials from 10 to 300 Hz
Bibliographic record
Abstract
Accurate determination of the complex shear modulus of soft tissues and soft-tissue-like materials in the 10-300 Hz frequency range is very important to researchers in MR elastography and acoustic radiation force impulse (ARFI) imaging. A variety of instruments for making such measurements has been reported, but none of them is easily reproduced, and none have been tested to conform to causality via the Kramers-Kronig (K-K) relations. A promising linear oscillation instrument described in a previous brief report operates between 20 and 160 Hz, but results were not tested for conformity to the K-K relations. We have produced a similar instrument with our own version of the electronic components and have also accounted for instrumental effects on the data reduction, which is not addressed in the previous report. The improved instrument has been shown to conform to an accurate approximation of the K-K relations over the 10-300 Hz range. The K-K approximation is based on the Weichert mechanical circuit model. We also found that the sample thickness must be small enough to obtain agreement with a calibrated commercial rheometer. A complete description of the improved instrument is given, facilitating replication in other labs.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".