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糖尿病视网膜病变患者全视网膜激光光凝治疗后疼痛感觉的问卷评估

2014· article· de· W3028689865 on OpenAlexaboutno aff
程华, 张素华, 初悦美, 柳玉娟

Bibliographic record

VenueZhonghua yandibing zazhi · 2014
Typearticle
Languagede
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.026

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.

Opus teacher head0.026
GPT teacher head0.314
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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