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Record W1973986154 · doi:10.1080/02652030701551826

Mycotoxins in breakfast cereals from the Canadian retail market: A 3-year survey

2008· article· en· W1973986154 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFood Additives & Contaminants Part A · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsManitoba HealthHealth Canada
FundersCanadian Food Inspection Agency
KeywordsZearalenoneMycotoxinOchratoxin AAflatoxinFood scienceToxinRetail marketBiologyToxicologyBusiness

Abstract

fetched live from OpenAlex

One hundred and fifty-six samples of breakfast cereals were collected from the Canadian retail marketplace over a 3-year period. The samples were analysed for the mycotoxins deoxynivalenol, nivalenol, HT-2 toxin, zearalenone, ochratoxin A, and fumonisins B1 and B2 to contribute to dietary exposure estimates in support of the development of Canadian guidelines for selected mycotoxins in foods. The samples included corn-, oat-, wheat- and rice-based cereals, as well as mixed-grain cereals, and were primarily from North American processors. Overall, deoxynivalenol was the most frequently detected mycotoxin--it was detected in over 40% of all samples analysed. Fumonisins and ochratoxin A were each detected in over 30% of all samples. Zearalenone was detected in over 20% of all samples. Nivalenol and HT-2 toxin were each detected in only one sample. The survey clearly demonstrated regular occurrence of low levels of multiple mycotoxins in breakfast cereals on the Canadian market.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.037
GPT teacher head0.215
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it