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Record W2777574563

Austria’s economy will grow by 2¾% in 2017

2017· article· en· W2777574563 on OpenAlex
Gerhard Fenz, Friedrich Fritzer, Martin Schneider

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMonetary Policy & the Economy · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGerman Economic Analysis & Policies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)EconomicsBoomReal gross domestic productEconomyMacroeconomicsGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

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%.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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.

Opus teacher head0.036
GPT teacher head0.240
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it