Volatile metabolites associated with one aflatoxigenic and one nontoxigenic <i>Aspergillus flavus </i>strain grown on two different substrates
Bibliographic record
Abstract
Aflatoxigenic and non-toxigenic Aspergillus flavus strains were grown on corn and on peanut substrates. Microbial volatile organic compounds (MVOCS) were collected by trapping headspace volatiles using thermal desorption tubes (TDT) packed with Tenax® TA and Carbotrap™ B. Samples were collected at various fungal growth stages. Trapped compounds were thermally desorbed from the adsorbent tubes, separated by gas chromatography, and identified by mass spectrometry. The fungal stage did not have many differences in the MVOCs but the concentrations of some volatiles changed over time depending on the substrate. Volatiles that were associated with both the aflatoxigenic A. flavus strain and the nontoxigenic strain on both substrates included: ethanol, 1-propanol, butanal, 2-methyl-1-propanol, 3-methylfuran, ethyl acetate, 1-butanol, 3-methylbutanal, 3-methyl-1-butanol, propanoic acid-2-methyl-ethyl-ester, 2-methyl-1-butanol, 1-pentanol, 2-pentanol, 3-methyl-3-buten-1-ol, benzaldehyde, 3-octanone, 2-ethyl-1-hexanol and octane. Volatiles that were associated only with the aflatoxigenic A. flavus strain included: dimethyl disulfide and nonanal. Volatiles that were associated only with the nontoxigenic A. fl avus strain included: hexanal, 1-hexanol, 1-octene-3-ol, 1-octen-3-one and 2-pentyl furan.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".