EUROFRAME - European Forecasting Network. Economic Assessment of the Euro Area: Forecasts and Policy AnalysisAutumn Report 2006. Special Policy Issue: Macroeconomic Differentials and Adjustment in the Euro Area: Stylised Facts and Policy Implications. September 2006
Bibliographic record
Abstract
Euro Area growth has picked up in the first six months of the year, with GDP growing by 0.8 per cent in the first quarter (quarter-on-quarter) and 0.9 per cent in the second quarter. This represents a considerable improvement on the average growth of just 0.5 per cent in the second half of 2005. The upturn was expected six months ago, but has been somewhat stronger than anticipated. This revision is due to unexpectedly strong export and investment growth in the Euro Area which has been boosted by unusually prolonged period of strong world economic growth. We do not expect growth to accelerate further in the second half of the year and anticipate a deceleration in growth from the last quarter. Overall, Euro Area GDP growth is expected to be 2.6 per cent for 2006.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".