Bibliographic record
Abstract
The beginning of 2010 brought good economic news to Japan, which has seen only lackluster growth for the past two decades. Although the country's debt load and deflation remain serious problems, the world's second largest economy reportedly grew in the last quarter of 2009. But that does not mean that Japan is on a route to long-term recovery. Although the science budget for fiscal year 2011 was not severely cut, a worrisome sign was the government's attempts to freeze investment in Japan's science infrastructure (for example, supercomputing) and reduce spending on earth sciences, cosmology, and other fields. These were avoided through the protests of prominent Japanese scientists. The lack of political interest in bolstering investment in science and technology indicates misguided thinking. There is therefore a growing awareness in the Japanese research community that scientists need to become more involved in formulating the country's science policy and in guiding young scientists into international networks that will support a successful global economy for Japan.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".