Bibliographic record
Abstract
目的探讨饮酒与Barrett食管发生的关系。方法系统检索PubMed、EMBASE、中国生物医学文献数据库(CBM)、中国期刊全文数据库(CNKI)等数据库。对纳入研究的文献采用Newcastle-Ottawa量表进行质量评价,根据研究类型、地域、资料来源、饮酒种类分亚组进行分析,综合定量评价饮酒与Barrett食管的关系。结果共纳入16篇文献(病例对照研究13篇,队列研究3篇)累积Barrett食管3 961例,对照11 748例。Meta分析结果显示队列研究亚组中,与不饮酒者相比,饮酒者Barrett食管发病风险OR为1.27(95%CI:1.03～1.58,P=0.03);亚洲地区亚组饮...
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.013 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".