Survey of aflatoxins in beer sold in Canada Part A Chemistry, analysis, control, exposure & risk assessment
Bibliographic record
Abstract
Between March 1998 and March 2002, 304 samples of domestic (Canadian) and imported beers from 36 countries were picked up for the determination of aflatoxins B1, B2, G1 and G2. Twelve samples were positive with aflatoxins greater than the limit of quantitation (LOQ) (aflatoxin B1, 4.4 ng l(-1); aflatoxin B2, 3.4 ng l(-1); aflatoxin G1, 11.2 ng l(-1); and aflatoxin G2, 6.2 ng l(-1)). Five samples from Mexico, two samples from Spain and one from Portugal contained aflatoxin B1. Four samples from India contained aflatoxins B1 and B2. The remaining samples contained less than the LOQ for aflatoxins B1, B2, G1 and G2. The analytical method for this survey was based on that of Scott and Lawrence (Scott PM, Lawrence GA. 1997. Determination of aflatoxins in beer. Journal of AOAC International 80:1229-1234.). Aflatoxins B1, B2, G1 and G2 were determined at parts per trillion (ng l(-1)) levels in beer by immunoaffinity column cleanup followed by derivatization with trifluoroacetic acid and reversed-phase liquid chromatography with fluorescence detection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".