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Record W2279046396 · doi:10.21098/bemp.v18i4.572

QUARTERLY OUTLOOK ON MONETARY, BANKING, AND PAYMENT SYSTEM IN INDONESIA: QUARTER I, 2016

2016· article· en· W2279046396 on OpenAlexaboutno aff
TM Arief Machmud, Syachman Perdymer, Muslimin Anwar, Nurkholisoh Ibnu Aman, Tri Kurnia Ayu K, Anggita Cinditya Mutiara K, Illinia Ayudhia Riyadi

Bibliographic record

VenueBulletin of Monetary Economics and Banking · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Investment (military)Consumption (sociology)EconomicsFinancial systemMonetary economicsGovernment (linguistics)Financial stabilityFinancial marketCapital (architecture)Private consumptionBusinessFinanceFiscal policy

Abstract

fetched live from OpenAlex

The growth of domestic economy in Indonesia is lower than forecasted in first quarter of 2016.However, the economy is expected to revive and will grow higher in the next quarter, with a well maintained financial system stability. The limited growth of government consumption as well as private investment are the main reason for the slower growth in this quarter, eventhough the government spending on capital goods accelerates. The growth of private consumption remains high with reasonable price movement. With the increase of several commodities’ export, the external performance of export in aggregate also increased. On the other hand, the financial system stability was stable due to viable banking system and better financial market performance. The stability of Rupiah was well maintained, supported by positive expectation on domestic economy and the lower risk of the global financial market.

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)0.001
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.008

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 head0.010
GPT teacher head0.168
Teacher spread0.158 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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