Quantitative Analysis of Mixer‐Type Rheometers using the Couette Analogy
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Bibliographic record
Abstract
Abstract A procedure based on a Couette analogy, to quantitatively analyze torque/rotor speed data in order to extract viscosity/shear‐rate curves using non‐conventional geometries is presented. It is first validated using a relatively simple geometry for which the equivalent internal radius used in the analogy can be analytically obtained. The results showed that the equivalent internal radius depends only slightly on the nature of the fluid and that there is an optimal radial position r * in the analog Couette gap where the calculations can be easily performed for computing the viscosity/shear‐rate data from torque/rotational speed data. The experimental results with complex geometries and complex fluids are found to coincide, within experimental errors, with those obtained using standard geometries over a wide range of shear rates. The approach is also found to be very useful to evaluate shear‐rate and viscosity data in Couette viscometers when large gaps are used with non‐Newtonian fluids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it