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Record W2061210167 · doi:10.3920/wmj2008.x003

Microbial transformation of trichothecene mycotoxins

2008· article· en· W2061210167 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.

Bibliographic record

VenueWorld Mycotoxin Journal · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
Fundersnot available
KeywordsTrichotheceneMycotoxinMicroorganismFusariumBiologyAnimal healthGenerally recognized as safeBiotechnologyFood safetyVomitoxinBacteriaFood scienceMicrobiologyToxicologyZearalenoneBotany

Abstract

fetched live from OpenAlex

Trichothecene mycotoxins produced by the Fusarium genus are highly toxic to humans and animals. They are commonly found in cereals worldwide, which is not only a concern for food safety, but also highly relevant to the livestock industry. Controlling trichothecenes in food and feed has been a challenge since the toxins are markedly stable under different environmental conditions. Thermal processing is usually ineffective, and chemical treatments generally are expensive and often result in side effects. Previous studies on innovative biological approaches, such as the use of microorganisms and enzymes, to convert the toxins into non or less toxic compounds have shown promise. This review will briefly describe the chemical structures and toxicity of trichothecenes, and examine the microorganisms, including both bacteria and fungi, from various natural sources that are able to detoxify the toxins as either mixed cultures or a pure culture of single isolates. Finally, challenges and innovative strategies in the development of technology to detoxify trichothecenes by microorganisms are described.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.202
Teacher spread0.183 · 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