Impedance properties of biomass in support of practical mensuration in rain gardens
Bibliographic record
Abstract
Impedance microbiology was explored to provide insights into how a sensor that can monitor the growth of bacteria in vegetated bioretention systems (rain gardens) may be designed for in situ, real-time use. The impedance properties of Pseudomonas Putida samples were monitored under AC signals of 100 mV peak-to-peak and sweeping frequencies of 20 Hz–300 kHz, to determine relationships between these properties and biomass in the laboratory. The capacitance of the samples was found to be the most sensitive impedance parameter, with average change in magnitude of 37% due to bacterial growth. For verification, optical density measurements were taken and calibrated by direct hemocytometry counts of similar samples, simultaneously with the impedance testing. The experiments revealed that exponential relationships enable a good estimate of the biomass available in the medium, based on the change in capacitance. The detection range of the proposed system (in the range of tested strain) is approximately ∼9.2 × 106 cells/mL to ∼5 × 108 cells/mL.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".