Bibliographic record
Abstract
2005年5月16-17日,由中华医院管理管理学会信息管理专业委员会和北京华卫医院发展研究中心联合举办的中美医院流程再造专题研讨会在北京21世纪饭店的一间会议厅举行,来自北京、山东、河北、江苏、陕西、湖北、辽宁等省、市近百名医院的管理者,认真聆听了美国罗斯大学医学中心教授李劲、美国Metis Advisory Group,Ltd公司总裁J.Christopher Newman、美国Anshen+Allen Architects(A+A)公司总裁兼CEO Roger Swanson、原北京和睦家医院院长Andrew S.Nevin,PhD、天津市人民医院院长吕文光、北京大学公共管理学院教授马谢民等所作的关于医院流程再造的专题讲座,讲座结束后,与会代表就此主题进行了热烈而有益的讨论.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".