Maxing Ganshi Soup Combined with Western Medicine Treatment of Bronchial Asthma,Randomized Parallel Group Study
Bibliographic record
Abstract
[Objective]Observe Ma Xing GanShi Tang combined with western medicine treatment of bronchial asthma treatment.[Methods]Using randomized controlled method,56 cases of inpatient / outpatient patients were randomly divided into two groups.Control group,28 cases of β2 agonist theophylline 0.2g / time,2 times / d;according to patient severity staging suck Rupumike aerosol,200 ～ 1000μg / d.Treatment group 28 cases Ma XingGan Shi Tang(Mahuang 15g,Shigao 30g,Xingren 20g,Gancao 10g);1 does / d,decoction 250 ～ 300mL,taking three times.Cold in the table to gypsum Nepeta,basil;wind chill temperature while relying on Canadian cattle next to the child,SSP;fever even add honeysuckle,Houttuynia,forsythia;constipation increased yellow;cough and bloody sputum plus blood over charcoal,cogongrass rhizome;appetite anorexia plus hawthorn,built song;kidney qi plus Guiyuan meat,walnut meat;dark purple tongue plus safflower,salvia.Western medicine with the control group.7d is a continuous course of treatment.Observation of clinical symptoms and adverse reactions.Continuous treatment of 3 courses,to determine efficacy.[Results]treatment group,20 cases markedly effective in 7 cases,1 case,the total effective rate 96.43%.Control group,10 cases markedly effective in 15 cases,3 cases,the total efficiency of 89.29%.Treatment group than the control group(P 0.05).[Conclusion]Ma XingGan Shi Tang combined with western medicine treatment of bronchial asthma,the effect is significant and should be introduced.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".