Direct Impedimetric Detection and Isolation of Bacillus Cereus using Modified Platinum Electrode
Bibliographic record
Abstract
This work proposes a technique for isolation of bacteria using magnetic nanoparticles. The magnetic nanoparticles that are prepared by a sol-gel method using citric acid and nano-ferrites are characterized for structural and morphology by X-ray diffraction (XRD) and Transmission electron microscope (TEM), respectively. The prepared nano-ferrites coated with poly vinyl alcohol (PVA) over platinum electrode are used for detection of Bacillus Cereus. The isolated bacterial cells from colloidal solution are treated with zinc ferrite for 12 h, and it is observed that the cells are coagulated with the nanoparticle when allowed to settle down. This is further filtered by different size of filter paper to get less than 0.1% of cells in water. Various electrochemical parameters like cyclovoltammetry (CV), sweep step function, Tafel plot, AC impedance are studied employing the modified platinum electrode. It is observed through CV graph that the peaks are formed at -0.25 V due to the oxidation of bacterial cells, which is further supported by sweep step function graph. Therefore, this is one of the economically efficient techniques to detect and isolate the Bacillus cereus from a colloidal solution.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".