Research on Prediction of China’s Population Development from 2008 to 2050
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
Population system is a typical grey system. In this paper, we establish two new grey models of population prediction: discrete grey increment model(DGIM) and grey increment model with new initial value(NGIM). By contrasting, we did simulation and test prediction through utilizing a large amount of data. The results indicate that the two new models prove more accurate than GM(1, 1) model and other models. According to the latest statistical data of China’s population from 1949 to 2007, we predict the population development of China up to the year 2050 based on the two new models. Evidence shows that at the end of 2008, 2010, 2020, 2030, 2040 and 2050 the total population will reach 1.32789, 1.3403, 1.3917, 1.428, 1.454 and 1.472 billion, respectively.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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