Method development for quantification of iodine in food for special medical purposes (FSMP) after microextraction by Bi-SBA-15 based matrix solid-phase dispersion
Bibliographic record
Abstract
In this study, bismuth (Bi)-embedded SBA-15 mesoporous silica was synthesized, characterized and used as adsorbent for matrix solid phase dispersion (MSPD) of iodine in whole nutritional formula foods, subsequently determined by inductively coupled plasma mass spectrometry (ICP-MS). The experimental conditions for the MSPD were firstly investigated, utilizing a mass ratio of sample to Bi-SBA-15 at 3:3, with 200 mM [C12mim]Br as the elution solvent and a grinding time of 2 min. Meanwhile, interference studies revealed that the presence of cations (K + , Na + , Ca 2+ ) could significantly decrease the analytical signal, prompting the implementation of a cation-exchange procedure. Under optimum experimental conditions, analytical performance of Bi-SBA-15 based MSPD-ICP-MS for iodine detection was evaluated in terms of limit of detection (LOD) and limit of quantification (LOQ), which was 0.03 μg/kg and 0.21 μg/kg respectively. To evaluate the accuracy and applicability of this method, a recovery study was conducted on commercial foods for special medical purposes (FSMP), with recoveries ranging from 95.5 % to 106 %. Therefore, the application of SBA-15 based matrix solid-phase dispersion would attract significant attention for separation and preconcentration of total iodine in complex food samples such as foods for special medical purposes (FSMP).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".