A high throughput ambient mass spectrometric approach for identifying the poaching of wild american ginseng
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.
Bibliographic record
Abstract
Abstract Rapid identification is critically important in the protection of endangered species listed under the Convention on International Trade in Endangered Species (CITES). One such species is American ginseng ( Panax quinquefolius ), whose remaining wild populations are vulnerable to the effects of poaching. Direct Analysis in Real Time Time-of-Flight Mass Spectrometry (DART-ToF MS) is a mature but underutilized forensic tool suitable for rapidly analyzing plant materials. This tool offers greater convenience over alternative species identification methods commonly requiring extensive sample preparation and instrument run times. In the current study, four categories of ginseng, including wild and cultivated American ginseng, Korean ginseng ( P. ginseng ), and Chinese ginseng ( P. notoginseng ), were analyzed by DART-ToF MS. The collected mass spectra were visually compared by heat map prior to application of multivariate statistical analysis to cluster sample groups, yielding a two-step identification model capable of identifying the origin of blind quality assurance samples. With fast sample preparation, data acquisition, and statistical analysis, DART-ToF MS shows great potential as a forensic screening tool in combating poaching and illegal trade of endangered and CITES-listed species such as wild American ginseng.
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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 | 0.001 | 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