Czech pre-2009 growth rate may return
Bibliographic record
Abstract
Subject Leaders and laggards among CE economies. Significance Economic growth remained solid in the Czech Republic and Poland in the first half of 2015. Czech GDP grew by 4.4% annually in April-June, well above expectations and the EU average; in Poland, the economy slowed marginally in the second quarter compared to the first. In Hungary, industrial production data for July underline the slowdown in GDP in the second quarter. Nevertheless, domestic demand has recovered across the Central European (CE) region, following the 2008-09 crisis setback; net exports' contribution to headline growth is far smaller than in recent years. Impacts Drops in external demand in the EU and Asia, and in industrial performance, pose the most significant downside risks. After a disappointing 2015, Poland and Hungary should bounce back in 2016, supported by rising employment as slack in the economy recedes. As the risk of deflation subsides, the Czech Republic is expected to post the strongest rates of growth across the region in 2016-17.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.096 | 0.070 |
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".