Comparison of Ion-Specific Electrode and High Performance Liquid Chromatography Methods for the Determination of Iodide in Milk
Bibliographic record
Abstract
Two methods for the determination of I- in raw and processed milk were examined. A simple ion-specific electrode (ISE) method was compared against a more complex HPLC reference technique. Accuracy and precision were evaluated both within and between the 2 methods. Both methods yielded good recoveries for Ion spiked samples, ranging from 87 to 114% for ISE and 91 to 100% for HPLC. Within-run repeatability and between-run reproducibility were superior with the HPLC method, but were still more than acceptable with the ISE technique. Overall agreement of paired results between ISE and HPLC methods was good (r2 = 0.85 on raw herd milk; r2 = 0.84 on processed milk). The ISE method had a significant positive bias relative to the HPLC reference method. Both methods lend themselves well to the measurement of I- in raw or processed milk. Given its relatively low cost and ease of use, the ISE method is well suited as a screening method. The impressive accuracy, precision, selectivity, and limit of detection of the HPLC technique make it an ideal confirmation method.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".