Rapid classification and identification of chemical compositions of Pu-zhi-hui-ling decoction by UHPLC-Q-Orbitrap HRMS
Bibliographic record
Abstract
Pu-zhi-hui-ling decoction (PZHLD) is a traditional Chinese medicine (TCM) formula for the treatment of Alzheimer's disease (AD), but its chemical composition has not been reported. In this study, we aimed to establish a mass spectrometry (MS) analysis method for rapid classification and identification of the chemical constituents in PZHLD. The sample was analysed by ultrahigh-performance liquid chromatography coupled to quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). The chemical constituents of PZHLD were identified based on accurate MS data, fragmentation characteristics of MS/MS, and reference information described in the literature. A total of 123 chemical constituents were identified. In addition, we summarised the fragmentation pathways of the chemical constituents in PZHLD. Our finding might lay the foundation for the further pharmacodynamic study and clinical application of PZHLD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".