Classification
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The biggest contribution to the vigorous growth of the Austrian economy in 2006 was made by manufacturing. The total value added surpassed the previous year's level by 7.5 percent in real terms – the highest rate of increase in years. Industrial production mainly benefited from strong export demand. Exports of goods increased by 10.2 percent in real terms over the previous year's result, which primarily reflects the strength of economic growth in foreign markets, above all in the oil-exporting countries, Asia and North America, as well as the twelve new EU countries, but also in the rest of the European Union. Moreover, considering their prices and the quality of their products, domestic enterprises are highly competitive. The unit labour costs of the highly export-oriented Austrian manufacturers dropped by 2.3 percent against those of their trading partners in 2006. In the course of the year, the strong expansion of production resulted in a substantially higher utilisation of capacities (up from 81.3 percent in the fourth quarter of 2005 to 84.3 percent in the fourth quarter of 2006). Excellent earnings, favourable sales expectations, and the high utilisation of capacities encouraged many enterprises to step up their capital expenditure on plant and equipment by a considerable amount (+5.3 percent). Despite the extraordinary increase in hourly productivity (+6.9 percent), the goods-producing sector recruited new labour for the first time since 2001.
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 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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it