Bibliographic record
Abstract
在糖尿病视网膜病变(DR)患者全视网膜激光光凝(PRP)治疗过程中,激光可能触及分布于脉络膜下间隙的睫状神经,出现治疗眼刺痛、胀痛[1].这种疼痛常常困扰患者接受治疗并可能带来其他一些消极影响.要对其疼痛进行管理,准确的疼痛评估是关键性的第一步.临床上采用的行为疼痛测定法、口述等级评分法、数字分级法和疼痛问卷表等,仅将疼痛的主观感觉客观化,而缺乏精确数值[2].在国际公认的描述疼痛量表McGill问卷表基础上简化而来的简式McGill疼痛问卷表(SF-MPQ)信度高、效度好、简便易行,适用证广泛,是一种有实用价值的测痛工具[3].为此,本研究利用SF-MPQ评估了DR患者在PRP治疗过程中的疼痛情况.现将结果报道如下. 关键词：激光凝固术/副作用;疼痛测定 分类号：R774
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".