효과적인 민간부문 기술혁신 지원을 위한 공공조달시장 제도 개선 방안
Bibliographic record
Abstract
Ⅰ. 서론 1. 연구의 배경 및 목적 2. 연구의 내용 3. 연구방법 Ⅱ. 패스트트랙 I과 패스트트랙 II 제도의 문제점 및 개선방안 1. 제도 도입 목적과 현황 2. 캐나다의 BCIP(The Build in Canada Innovation Program) 3. 주요 선진국의 연구개발 성공제품 조달 정책 4. 문제점 및 개선방안 Ⅲ. 중소기업제품 인증이 공공조달시장에 주는 효과 분석 1. 혁신 촉진을 위한 공공조달제도 소개 2. 인증된 중소기업 기술개발제품 거래 현황 3. 중소기업 기술개발제품 인증이 공공조달에 미치는 영향 분석 Ⅳ. 결론
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.286 | 0.390 |
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".