Study on Sustainable Development of Shenyang Expo Park and Innovation of Management
Bibliographic record
Abstract
Shenyang China International Horticulture Exposition 2006 was a world meeting, which gains most public attention in the world. Taking this chance, Shenyang shows to the whole world its new image as a modern metropolis. In order to do further research about the development of Shenyang Expo Park; this article explore and study from the following four aspects, in terms of the awareness of sustainable development, sustainable increase factors, the issues of sustainable and innovation of management, ultimate goal lies in offering a clear idea for the healthy, sustainable and steady development of Shenyang Expo Park. Key words: Shenyang, Shenyang Expo Park, Sustainable Development Resume: L’exposition internationale de l’horticulture de Shenyang en Chine 2006 est une reunion mondiale, qui attire l’attention du public dans le monde. En profitant de cette occasion, Shenyang expose au monde entier sa nouvelle image comme un metropole moderne. Afin de mener des recherches approfondies sur le developpement du Parc d’expo de Shenyang, le present article procede a l’etude sous les quatre aspects suivants : la conscience du developpement durable, les facteurs de croissance durable, le resultat du developpement durable et l’innovation de management. L’objectif ultime consiste a offrir une idee claire du developpement sain, durable et stable du Parc d’expo de Shenyang. Mots-Cles: Shenyang, Parc d’expo de Shenyang, developpement durable
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".