GC-HRTOF-MS dataset of metabolites extracted from sorghum and ting (a fermented product) produced using two strains of Lactobacillus fermentum (singly and in combination)
Bibliographic record
Abstract
This data article reports the untargeted metabolite profile of whole grain sorghum (Sorghum bicolor L.) and fermented ting samples obtained using two strains of Lactobacillus fermentum. The sorghum grains were obtained from Agricol Johannesburg (South Africa) and fermentation was done at 34 °C for 24 h. Controlled fermentation with two Lactobacillus fermentum strains (L. fermentum FUA 3165 and L. fermentum FUA 3321), was done using the strains singly and in combination. The samples obtained thereafter were freeze-dried and acetonitrile/methanol/water (v/v/v) were used as extraction solvent, before analyses on a gas chromatography high resolution time of flight mass spectrometry (GCHRTOF-MS) system. Data obtained showed the presence of different compounds, classified into metabolite groups such as acids, alcohols, benzenes, furan, esters, hydrocarbons, terpenes, phytosterols, etc., with their retention time, molecular formula, observed mass and average peak areas reported herein. These data can be used for finding biomarkers for sorghum and their derived fermented products.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".