Bibliographic record
Abstract
Abstract The “new era”, a term introduced by President Xi Jinping, may also be identified as the Xi era, during which China will be transformed from a moderately well‐off to a strong and wealthy nation. In the new era, the Chinese Government will deepen economic reform, widen economic opening and enhance the quality of economic growth. / Our projections show that by 2020, Chinese real GDP per capita, in 2017 prices, will exceed US$10,000, an economic development milestone. By 2031, Chinese real GDP will surpass US real GDP (US$29.4 trillion vs US$29.3 trillion), making China the largest economy in the world. However, Chinese real GDP per capita will still lag behind the US significantly, amounting to only one‐quarter of that of the United States. By 2050, Chinese real GDP will reach US$82.6 trillion, compared to US$51.4 trillion for the United States. However, in terms of real GDP per capita, China will still lag significantly behind, at US$53,000, slightly less than the current level of US real GDP per capita, compared to US$134,000 for the United States.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".