A Literature Review on the Research of Circular Economy-Based Green MICE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The circular economy is a mode of economic development centered on high efficient and cyclic utilization of resources, characterized by low input, high efficiency and low emission. “3R” is the most basic practical operating principle of circular economy. The circular economy integrates the cleaner production and the cyclic utilization of wastes. The green MICE has become one of the important industries of developing circular economy. Ping Hu (2006), Ming-Gui Sun (2006), Wei-Dong He (2009), etc. defined the green MICE respectively. As for the literature review on the researches of green MICE, the foreign scholars and countries focus on the construction of guides to the MICE (Meeting) and of ecological venues, such as Cathy Crisci (2009), the US “Meeting Industry Committee”(2003), Canada National Environment Research Council and Green Meeting Committee, Germany, the UK, France, etc. While in China, we focus on the research of green MICE’s development and approach of practice, such as Ming-Gui Sun & Hong-Yuan Zhang (2006), Cheng Yan (2007), Mei-Liang Cai (2008) and Wei-Dong He (2009), etc. Concluded from the literature review, the research of evaluation system of green MICE will be the future task.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it