Discrimination of Chuanminshen violaceum Sheh et Shen from different regions based on fatty acid profiles of roots and leaves
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Objectives The purpose of this paper was to construct a reliable methodology to discriminate the geographical origins of Chuanminshen violaceum Sheh et Shan planted in different regions in Sichuan, China. Materials and methods Fatty acid profiles of roots and leaves of C. violaceum planted in various regions of Sichuan Province in China, namely Guangyuan (GY), Langzhong (LZ), Jintang (JT), Bazhong (BZ), and Shuangling (SL), were determined using GC-MS followed by multivariate statistical analyses, including orthogonal partial least-squares discriminant analysis and hierarchical clustering analysis. Results Leaves of C. violaceum showed the highest contents of hexadecatrienoic acid (3.21 g/kg), linoleic acid (6.62 g/kg), and α-linolenic acid (7.24 g/kg), which were all higher than those contained in roots. Chuanminshen violaceum samples collected from LZ, JT, and GY could be clearly distinguished based on fatty acid profiles of leaves and those collected from LZ, GY, and BZ could be clearly distinguished based on fatty acid profiles of roots. Conclusions Chemometric method is used as a potential approach for analyses of fatty acid profiles of roots and leaves to control the quality of C. violaceum and their powered products.
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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) | 0.000 | 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) | 0.000 | 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 it