Austria’s economy will grow by 2¾% in 2017
Bibliographic record
Abstract
In the first half of 2017, Austria’s economy gathered further momentum. With growth rates by 0.8% in both the first and the second quarters, Austria recorded its strongest economic growth in six years. The broad-based cyclical upswing is being underpinned by both domestic and foreign demand and will continue in the second half of the year. Based on its quarterly forecasting exercise, the Oesterreichische Nationalbank (OeNB) expects real GDP to expand (quarter on quarter) by 0.7% in the third quarter and by 0.6% in the fourth quarter of 2017. For the year as a whole, economic growth in Austria will thus come to 2¾%. Compared with the OeNB’s June 2017 outlook for GDP growth, this implies an upward revision of 0.5%. Distinctly higher growth rates were last recorded in the boom period of 2006 and 2007, when economic growth accelerated to 3½%.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.031 |
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".