Proportional Microvolume Capacitive Liquid Level Sensor Array
Bibliographic record
Abstract
A sensor array has been developed for use with laboratory automation to permit closed-loop control of liquid levels in a multiwell microplate geometry. We extended a simple electrical model for non-contact capacitance-based fluid sensors to describe a fluid-level dependency. The new model shows that a charge-transfer based capacitance transducer, employing a liquid-specific calibration, can be used to obtain an output signal that varies linearly with the liquid level. The calibration also compensates for liquid-to-liquid conductivity and permittivity differences. A prototype 3times3 sensor array was built and tested using NaCl and ethanol solutions to simulate the range of conductivity and permittivity typical in biological and chemical research. Calibrated output signals were linear with liquid volume for all tested solutions (R2> 0.92). Measurement error averaged 1.3% (2.0 muI) with a standard deviation of 6.0% (9.0 muI). These results demonstrate the feasibility of developing a microvolume sensor array in essentially any MtimesN microplate geometry
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".