Strengthening the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR): a Korean translation of explanation and elaboration
Bibliographic record
Abstract
멘델 무작위화(Mendelian randomization, MR) 연구는 조절 가능한 노출(modifiable exposure)이 건강결과에 미치는 인과효과(causal effect)를 더 잘 이해하게 해 주지만, 그 근거는 종종 보고가 불충분함으로 인하여연구 결과의 해석과 적용에 한계가 있을 수 있다. 보고지침은 흔히 무슨 연구를 하고 무엇을 발견했는지 독자가 쉽게 이해하도록 돕는다. STROBE-MR(관찰연구의 멘델 무작위화를 활용한 보고지침)은 MR 연구를 명확하고 투명하게 보고하도록 돕는다. STROBE-MR을 논문 작성에 활용하면 독자, 심사자, 학술지 편집인이 MR 연구의 보고 품질과 완성도를 평가하는 데 도움이 될 것이다. 이 글은 STROBE-MR 체크리스트 20개 항목의 의미와 근거를 설명하고, 각 항목마다 사례를 제시해 독자가 잘 이해할 수 있는 논문 작성법을 설명하려고 하였다.
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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 | 0.493 | 0.718 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".