Preconcentration of codeine in pharmaceutical and human urine samples by multi-walled carbon nanotubes and its spectrophotometric determination
Bibliographic record
Abstract
A rapid and efficient solid phase extraction method was established for the preconcentration of codeine prior to its simple determination by spectrophotometry. The extraction process is based on the multi-walled carbon nanotubes (CNTs) containing –COOH functional groups. These CNTs showed a great affinity for the low quantities of codeine in certain condition. Various extraction factors including buffer type, concentration and its pH, ionic buffer, incubation time, and eluent were optimized to achieve high sensitivity. The calibration graph was linear in the codeine concentration range of 0.001–4 mg·L −1 , with a detection limit (3s) of 0.4 μg·L −1 . The relative standard deviation (RSD %) for the repetitive determination of 0.01, 0.5, and 2 mg·L −1 codeine (n = 5) were 1.56%, 2.01%, and 1.63%, respectively. Furthermore, comparison with other reported methods showed that the presented method has suitable characteristics. Finally the method was successfully used to accurately determine codeine in pharmaceutical and human urine samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".