Bibliographic record
Abstract
The goal of the present study was to discuss the possibility of ultra-performance convergence chromatography( UPC2) for separation and determination of vitamin C in infant formula milk powder by the columns with different stationary phases. Finally,the Waters CSH Fluoro-Phenyl( 3. 0 × 100 mm,1. 7 μm)column was used in the experiments. A gradient elution was performed with the mixed mobile phase of supercritical CO2 and methanol( added 0. 1% H3PO4)) at a flow rate of 0. 6 m L/min. The UV detector was set at a wavelength of 245 nm. The limit of detection was 5 mg / L and the calibration linear range was 5 ~200 mg / L. The average recoveries were 90. 7% ~ 95. 4%,and the relative standard deviation ranged from1. 9% to 2. 8%. Then,we compared the proposed method with standard GB 5413. 18-2010( National food safety standard: Determination of vitamin C in foods for infants and young children,milk and milk products).The results showed that the accuracy and precision of two methods could satisfy the requirement for the determination of Vitamin C. In the standard method,the fluorescence intensity was affected by numerous factors,most of which are difficult to control,thus leading to high requirement of operator skills. In the comparison,the proposed method has the advantages of high efficient, rapid, simplicity, high sensitivity and simple pretreatment. The method was time-saving,low cost and eco-friendly.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".