Synthesized Cobalt Tetroxide-Graphene Composite Film by Electrospinning and Modified Glassy Carbon Electrode for Ofloxacin Determination
Bibliographic record
Abstract
The purpose of this study was to determinate ofloxacin, the approach of electrospinning and electrochemical was adopted, metal oxide cobalt tetroxide (Co3O4)/graphene (GR) nanomaterials were electrodeposited on the surface of glassy carbon electrode, then prepared a new type of nanocomposite electrode (Co3O4/GR/GCE), it was successfully used to measure ofloxacin. The experiments show that the surface morphology of the modified electrode was characterized by scanning electron microscopy, and the Co3O4 nanoparticles and GR could be well modified on the surface of the glassy carbon electrode. The determination conditions of ofloxacin were optimized by the differential pulse voltametry (DPV). Under the optimal conditions, the linear relationship ranged from 0.45 to 170 μM, and the minimum detection limit was 0.16 μM (S/N = 3). Moreover, the recovery rate in the actual drug was good, and the relative standard deviations were all less than 5%. The impacts of the obtained results indicate that the modified electrode has good electrocatalytic performance for ofloxacin, and has good repeatability and practicability, and can significantly improve the detection sensitivity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".