Investigation of action analysis and research approach of supramolecule on(homeo-)sensitization responses for the Chinese matria medica injection
Bibliographic record
Abstract
Objective To analyze the research status of Chinese materia medica injection (CMMI), and to investigate their immunotoxicities owning to supramolecular structure and the suitable research approach. Methods The research status of the CMMI, especially their safety research was summarized, and possibly existing supramolecular forms in the CMMI were analyzed in order to explain the supramolecular structure actions in the research of the CMMI immunotoxicities, as the research approach as well. Results There were mainly two kinds of immunotoxicity(senstization and homeo-sensitization responses) and the sensitinogens might be unimolecule and their metabolites, especially the supramolecular structures formed from the single compounds that can build the supramolecular structure by complex, composite, chelation, inclusion, neutralization, self-assembly and chemical reaction, which could markedly improve their apparent molecular weight and immunogenicity. The supramolecular structures would be reserved in maximum in injection administration, whereas they would be disassembled in oral administration. Therefore, it was more easily to generate immunotoxicity by injection administration than the oral administration. Conclusion The material foundation of the CMMI consists of the supramolecular group mixtures including single molecules, which can be reserved in maximum by injection administration, but markedly changed by oral administration. The regularities and research approach of supramolecular action should be thought highly during the study of the CMMI safeties, which is the most essential for the CMMI distinguishing from the single ingredient injection.
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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) | 0.000 | 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) | 0.001 | 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 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".