Superhydrophilic graphene oxide/electrospun cellulose nanofibre for efficient adsorption of organophosphorus pesticides from environmental samples
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Superhydrophilic graphene oxide/electrospun cellulose nanofibre (GO/CNF) was synthesized, characterized and successfully used in a solid-phase membrane tip adsorption (SPMTA) as an adsorbent towards a simultaneous analysis of polar organophosphorus pesticides (OPPs) in several food and water samples. Separation, determination and quantification were achieved prior to ultra-performance liquid chromatography coupled with ultraviolet detector. The influence of several parameters such as sample pH, adsorption time, adsorbent dosage and initial concentration were investigated. SPMTA was linear in the range of 0.05 and 10 mg l −1 under the optimum adsorption conditions (sample pH 12; 5 mg of adsorbent dosage; 15 min of adsorption time) for methyl parathion, ethoprophos, sulfotepp and chlorpyrifos with excellent correlation coefficients of 0.994–0.999. Acceptable precision (RSDs) as achieved for intraday (0.06–5.44%, n = 3) and interday (0.17–7.76%, n = 3) analyses. Low limits of detection (0.01–0.05 mg l −1 ) and satisfactory consistency in adsorption (71.14–99.95%) were obtained for the spiked OPPs from Sungai Pahang, Tasik Cheras, cabbages and rice samples. The adsorption data were well followed the second-order kinetic model and fits the Freundlich adsorption model. The newly synthesized GO/CNF showed a great adsorbent potential for OPPs analysis.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 it