Development of an analytical method for the quantification of bromoform in milk using gas chromatography–mass spectrometry
Bibliographic record
Abstract
Enteric methane production by ruminants contributes significantly to global greenhouse gas emissions. Seaweeds are rich in bromoform, which are known to strongly reduce methane emissions when included in animal feed. To ensure that seaweeds can be safely used for methane mitigation, there is a need to monitor bromoform residue in milk. The objective of this study was to develop and validate an analytical approach for quantifying bromoform in milk. QuEChERS-based extraction and clean-up with dispersive solid phase extraction were used followed by analysis with gas chromatography–mass spectrometry. The proposed method was validated: the limit of quantification (LOQ) was 0.21 μg L −1 , and recovery rates ranged from 86 % to 101 % with a precision <18.9 %. Twenty-two commercial milks were analyzed and contained bromoform residues at concentrations ranging from below the LOQ to 0.34 μg L −1 . This method is a reliable tool for monitoring the presence of bromoform in milk.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".