Variability of Cole-model bioimpedance parameters using magnitude-only measurements of apples from a two-electrode configuration
Bibliographic record
Abstract
Electrical impedance measurements have been widely researched to monitor physiological changes in fruits and vegetables in a nondestructive manner. Recently, the parameters of the Cole bioimpedance model (R0, R1, C, and α), an equivalent circuit that is widely used to represent the electrical impedance of biological tissues, were extracted using techniques without direct impedance measurements. In this study, the variability of the Cole parameters extracted from magnitude-only measurements (from 200 Hz to 1 MHz) of apples in a two-electrode setup was examined to understand the impact of electrode placement on the parameters evaluated using this technique. Eight electrodes were placed around the center latitudinal line of apples to collect seven sets of measurements from four different varieties (Granny Smith, Fuji, Red Delicious, and Spartan). The Cole impedance parameters were extracted in MATLAB from the collected measurements using a nonlinear least squares fitting method. These extractions indicated that the parameters R0 and R1 had the highest variability based on the electrode location, whereas the dispersion coefficient (α) had the lowest variability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".