The Membrane Sensors Sensitive to Fluoxetine - Optimization of the Analytical Parameters
Bibliographic record
Abstract
Background: The analytical characteristics of electrodes containing liquid PVC membrane depend on the purity of the electroactive material and the applied membrane solvents.Methods: Fluoxetine - one H-bond donor, formed ion-associated complexes with tetraphenylborate, tetrakis(4-chlorophenyl)borate and dipicrylamine. To confirm the quality and purity obtained complexes the elemental and TLC analysis were performed. The construction and general characteristics of fluoxetine ion-selective plastic membrane sensors, based on the use of a fluoxetine – tetrakis(4-chlorophenyl)borate ion-pair complex as electroactive material with 2-nitrophenyloctyl ether, bis(2-ethylhexyl)sebacate, bis(2-butylpentyl)adipate and 1-isopropyl-4-nitrobenzene as solvent mediators.Results: The electrode containing Fl-ClTPB-NPhOE (fluoxetine-tetrakis(4-chlorophenyl)borate-2-nitrophenyloctyl ether showed a linear response to fluoxetine at concentration ranges of 30.93 – 2.16 g·L-1 with a super Nernstian cationic slope 60.19 mV·decade-1.Conclusions: This Fl-ClTPB-NPhOE sensor was used for the potentiometric determination of the content of fluoxetine hydrochloride in pure form and pharmaceutical formula.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 0.001 |
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".