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Record W7038153508

Global economy is improving, but remains vulnerable to new and old headwinds that could derail growth, says UN report

2018· other· en· W7038153508 on OpenAlexaboutno aff

Bibliographic record

VenueEconomic Commission for Africa Knowledge Repository (Economic Commission for Africa) · 2018
Typeother
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsChinaQuarter (Canadian coin)World economyGlobal imbalancesPoint (geometry)GloomEmerging marketsDeveloped country
DOInot available

Abstract

fetched live from OpenAlex

Global economic growth should increase over the next two years with continuing signs of improvement, according to the United Nations World Economic Situation and Prospects 2014 (WESP) report, launched this week. The world economy experienced subdued growth for a second year in 2013, but some improvements in the last quarter have led to the UN’s more positive forecast. The euro area has finally ended a protracted recession. Growth in the United States strengthened somewhat. A few large emerging economies, including China and India, managed to backstop the deceleration they experienced in the past two years and veered upwards moderately. These factors point to increasing global growth.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.157
Threshold uncertainty score0.525

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0040.002
Scholarly communication0.0090.009
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1570.082

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 head0.022
GPT teacher head0.303
Teacher spread0.280 · 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
Published2018
Admission routes1
Has abstractyes

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