Multivariate model for the prediction of soluble condensed tannins in crude extracts of polyphenols from canola and rapeseed hulls
Bibliographic record
Abstract
Abstract The feasibility of using ultraviolet spectrophotometry to develop multivariate models for prediction of soluble condensed tannins (SCT) content in crude polyphenols extracts from canola and rapeseed hulls was investigated. The polyphenols were extracted from hulls using 70% (vol/vol) aqueous acetone. Partial least squares regression was used to correlate the spectral data of the crude polyphenols in methanol between 265–295 nm with the SCT content in hulls. Both the proanthocyanidin (P) and the vanillin (V) assays were used to provide reference data for creating the models. The predictive ability of the models is good, as indicated by the RPD values [the ratio of the standard deviation of data to the standard error of calibration (SEC) of above 5. Additionally, the SEC values suggest that P is superior to V in predicting the SCT content of hulls using this method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".