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Record W7015341608

Strong German economy leads European growth

2016· other· en· W7015341608 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2016
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicGerman Economic Analysis & Policies
Canadian institutionsnot available
Fundersnot available
KeywordsGerman economyPaceQuarter (Canadian coin)Investment (military)German governmentGermanGovernment (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

Europe's economy grew in the second quarter thanks to a stronger than expected showing by Germany. The 0.4 percent increase was better than economists expected. The German economy, Europe's biggest, grew four tenths of a percent in the second quarter. That's a slower pace than in the previous three-months but it's better than economists had forecast.It helped the 19-country eurozone economy expand by three tenths of a percent in the second quarter, even though Italy's economy saw no growth at all.Foreign trade exports grew while imports declined slightly.Consumer and government spending also supported growth, but investment - particularly in equipment and construction - was lower following a strong first-quarter showing.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0440.014

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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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