Research on the urban system of Three Georges Reservoir Area in northeastern Chongqing based on fractal theory
Bibliographic record
Abstract
Taking the 11 counties in Three Gorge reservoir area of Northeast Chongqing as an example and using the fractal theory,this article calculated the first index of the urban system and the fractal dimension of the city size distribution to explore the scale structure of the urban system,and evaluated the correlation dimension of the space structure to understand the spatial structure of the urban system.The results show that:1)the urban system in Three Gorge reservoir area of Northeastern Chongqing has fractal structure and fractal features;2)Wanzhou,the biggest city in the system,is of no obvious monopoly features and there are a number of middle-sized cities,with population distributing evenly in these cities;3)the cities and towns scatter in this area,with an ordinary spatial correlation among them.Finally,based on the results,this paper proposesd the following measures to optimize the urban system structure and function:to strengthen the main radiation role of Wanzhou as the first city,to develop the town-zone along the river,to speed up the construction of different characterized small towns and to consummate the transportation and information network.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".