Bibliographic record
Abstract
目的：运用简化McGill量表评定“项八针”法对神经根型颈椎病疼痛的影响。方法：60例神经根型颈椎病患者随机分为治疗组和对照组，每组30例。治疗组采用“项八针”法针刺治疗，对照组采用牵引疗法治疗，两组每周均治疗3次，1周为1个疗程，共治疗2个疗程。分别于治疗前、治疗1个疗程后及治疗2个疗程后运用简化McGill疼痛量表对疗效进行评估。结果：两组治疗1个疗程后、治疗2个疗程后的PRI感觉项、PRI情感项、PRI总分、VAS以及PPI评分均较治疗前明显降低，具有高度显著差异（ P＜0．01）；治疗1个疗程后，治疗组的PRI情感项及PPI评分改善率较对照组明显升高，具有显著差异（ P＜0．05），治疗组的PRI感觉项、PRI总分及VAS改善率较对照组明显升高，具有高度显著差异（P＜0．01）；治疗2个疗程后，治疗组的PPI评分改善率较对照组明显升高，具有显著差异（P＜0．05），治疗组的PRI感觉项、PRI情感项、PRI总分及VAS改善率较对照组明显升高，具有高度显著差异（ P＜0．01）。结论：“项八针”能明显减轻神经根型颈椎病患者的颈痛程度，缓解患者的负面情绪，临床治疗作用优于牵引疗法。
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".