Bibliographic record
Abstract
Ⅰ. 序論 1. 硏究의 必要性 2. 硏究目的 3. 硏究方法 Ⅱ. 인터넷 健康情報서비스의 理論的 背景 1. 인터넷 健康情報서비스의 意義 2. 인터넷 健康情報의 利用實態 및 質 管理: 旣存硏究 檢討 3. 健康情報 메타데이터의 活用 4. 웹 시스템의 品質保證 方法 Ⅲ. 主要 國家의 인터넷 健康情報서비스 動向 分析 1. 英國: NHS Direct Online 2. 美國: HealthFinder 3. 캐나다: Canadian Health Network 4. 濠洲: HealthInsite 5. 要約 Ⅳ. 主要 情報技術 動向 分析 1. 인터넷 情報檢索 方法 2. 시맨틱 웹 技術 3. 웹 서비스 技術 Ⅴ. 인터넷 健康情報서비스 利用實態 및 需要 分析 1. 調査槪要 2. 인터넷 健康情報 利用實態 分析 3. 健康情報 需要 分析 4. 要約 및 示唆點 Ⅵ. 인터넷 健康情報 게이트웨이시스템 基本計劃 1. 戰略計劃 2. 인터넷 健康情報 質 管理體系 3. 情報化 戰略計劃 (情報아키텍쳐 包含) Ⅶ. 인터넷 健康情報 게이트웨이시스템 開發 1. 2003年度 시스템 開發 2. 건강정보광장의 構成 및 機能 3. 건강정보광장의 設置 및 運營 Ⅷ. 結論 및 政策的 提言 1. 結論 2. 政策的 提言 3. 限界點 및 追加硏究 參 考 文 獻 附 錄
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.026 |
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.
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".