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Record W6940877935 · doi:10.1139/cjps2013-096

Fate of moniliformin during milling of Canadian durum wheat, processing, and cooking of spaghetti

2014· article· en· W6940877935 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsMycotoxinMyceliumFusariumBranSteamingFungal growth

Abstract

fetched live from OpenAlex

Tittlemier, S. A., Roscoe, M., Trelka, R., Patrick, S. K., Bamforth, J. M., Gräfenhan, T., Schlichting, L. and Fu, B. X. 2014. Fate of moniliformin during milling of Canadian durum wheat, processing, and cooking of spaghetti. Can. J. Plant Sci. 94: 555-563. Samples of clean Canadian durum were fortified with kernels damaged by Fusarium avenaceum at levels corresponding to the grading tolerances for Fusarium damaged kernels in Canadian durum wheat. Fusarium avenaceum produces the mycotoxin moniliformin (MON); the fortified durum samples contained MON ranging from 0.16 to 0.90 mg kg-1. The fate of MON was followed during milling of the fortified durum samples, as well as during the preparation and cooking of spaghetti made with the fortified durum. The majority of MON was associated with semolina, implying that removal of bran would not have a large impact on reducing MON concentrations. However, F. avenaceum DNA was more evenly distributed amongst the milling products, suggesting that MON underwent translocation from mycelium to endosperm in the damaged kernels. There was an apparent loss of MON when spaghetti was prepared from semolina. From an overall dietary exposure point of view, the cooking of MON-containing pasta in water will reduce dietary exposure to the water-soluble MON via leaching to the cooking water. However, the lack of quantifiable MON in samples prepared from higher grade Canada Western Amber Durum (which contained lower amounts of Fusarium damaged kernels) suggests that dietary exposure to MON from contaminated pasta is not likely to occur.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

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

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 head0.151
GPT teacher head0.203
Teacher spread0.052 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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