A fluid density sensor based on a resonant tube
Bibliographic record
Abstract
A fluid density sensor based on resonance frequency change of a metallic tube is presented. The sensor has been developed without using a complex micro-fabrication process. The sensor is able to identify fluid types/contaminations and improve the performance by reducing testing time, decreasing complexity of testing equipment and reducing sample sizes. The sensor can measure the resonance frequency of its own structure and determine the change in resonance frequency due to the subsequent sample inside the tube. Numerical modelling, analytical modelling and physical testing of a prototype sensor showed comparable results for both the magnitude and resonance frequency shift. The modelling results yielded a resonance frequency shift of 200 Hz from 9.87 kHz to 9.67 kHz after the water was filled into the tube. The actual testing illustrated a resonance frequency change of 280 Hz from 9.11 kHz to 8.83 kHz. The ultimate aim of the work is to determine resonance frequencies of desired samples at a level that could detect genetic disease on a cellular level.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".