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
Consider that 26.3 million people live in Shanghai and 20 million live in Beijing as of 2019. Now consider that these 46.3 million people live within an area of approximately 23,000 km². By comparison, Canada’s population in 2019 was 37.6 million and the area of Canada is approximately 10 million km². China is on the leading edge of smart-city projects because population density gives it little choice. China must take bold steps in terms of both technology and regulation to cope with the demands for social management, which these megacities create. Accordingly, about half of the Smart City Projects globally are in China. 
 Many smart cities pilot projects are underway across China addressing many infrastructures and other organizational concerns. One such organizational concern is coping with the solid waste generated in cities. China produces more than 300 million tons of solid waste per year, and much of it comes from its cities.
 
 This research project explores China's food and beverage delivery online platforms and the waste they cause. In 2019, this industry has developed rapidly, generating economic activity valued at ¥ 653.6 billion that year ($CAD 121 billion). Out of a total population of 1.4 billion, 460 million people are currently consumers of these online platforms. Most of these consumers live in China’s megacities. This consumption is not projected to decrease post-pandemic. The problem is that solid waste from this industry in 2019 weighed approximately 2.7 million tons.
 
 This paper analyzes reasons why the online food take-out industry has caused a plastic waste surge from the perspective of China's environmental legislation, law enforcement efficiency, and recycling subsidies. At the same time, through the case study of the German Packaging Law, this paper suggested on the management and recycling of Chinese take-out packaging were put forward.
 
 The Chinese government has issued national standards for the design and construction of smart cities. This paper explores how to use legal governance and supervision in smart city design and operation to assist in implementing environmental regulations to control the take-out waste. The take-out waste problem does not only exist in China. Almost all major cities in the world are facing this problem. China's experiences may provide a new path for the city's solid waste disposal and other environmental issues and lead the cities to explore more environmental protection possibilities.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it