A short-term projection for Japanese central government debt via WASD neuronet
Bibliographic record
Abstract
Japan has the highest debt-to-GDP ratio among advanced countries. Japanese central government debt has increased rapidly in the past 20 years. According to the data provided by Ministry of Finance, Japan, the total central government debt (TCGD) of Japan reached 1, 066,423.4 billion (December 31, 2016). This number refreshes the history record of Japanese central government debt. It is important to conduct a projection for the TCGD so that the government can make better fiscal policies and predict the risk in the future. In this paper, we conduct a ten-quarter projection for the TCGD of Japan via a three-layer feed-forward neuronet. The neuronet is trained successfully with the central government debt data from June 30, 1996 to December 31, 2016, provided by Ministry of Finance, Japan, in quarterly manner. Numerical experiments show four different trends of TCGD: slightly increasing trend, sharply increasing trend, decreasing-increasing trend and decreasing trend. The most possibility is that the TCGD increases slightly in short term. Furthermore, we conduct a relatively longer-term (i.e., twenty-four quarters) projection with the most possibility.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".