Surveys of rice sold in Canada for aflatoxins, ochratoxin A and fumonisins
Bibliographic record
Abstract
Approximately 200 samples of rice (including white, brown, red, black, basmati and jasmine, as well as wild rice) from several different countries, including the United States, Canada, Pakistan, India and Thailand, were analysed for aflatoxins, ochratoxin A (OTA) and fumonisins by separate liquid chromatographic methods in two different years. The mean concentrations for aflatoxin B(1) (AFB(1)) were 0.19 and 0.17 ng g(-1) with respective positive incidences of 56% and 43% (≥ the limit of detection (LOD) of 0.002 ng g(-1)). Twenty-three samples analysed in the second year also contained aflatoxin B(2) (AFB(2)) at levels ≥LOD of 0.002 ng g(-1). The five most contaminated samples in each year contained 1.44-7.14 ng AFB(1) g(-1) (year 1) and 1.45-3.48 ng AFB(1) g(-1) (year 2); they were mostly basmati rice from India and Pakistan and black and red rice from Thailand. The average concentrations of ochratoxin A (OTA) were 0.05 and 0.005 ng g(-1) in year 1 and year 2, respectively; incidences of samples containing ≥LOD of 0.05 ng g(-1) were 43% and 1%, respectively, in the 2 years. All positive OTA results were confirmed by LC-MS/MS. For fumonisins, concentrations of fumonisin B(1) (FB(1)) averaged 4.5 ng g(-1) in 15 positive samples (≥0.7 ng g(-1)) from year 1 (n = 99); fumonisin B(2) (FB(2)) and fumonisin B(3) (FB(3)) were also present (≥1 ng g(-1)). In the second year there was only one positive sample (14 ng g(-1) FB(1)) out of 100 analysed. All positive FB(1) results were confirmed by LC-MS/MS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".