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Record W7044292569

World Bank sets aside $200M to repair Lebanon's roads

2017· other· en· W7044292569 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2017
Typeother
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Quarter (Canadian coin)West bankSyrian refugeesRefugeeAside
DOInot available

Abstract

fetched live from OpenAlex

The World Bank says it has earmarked $200 million for repairing Lebanon's unsafe roads. The World Bank will help Lebanon repair it's unsafe roads.The bank said in a statement that it's earmarked 200 million dollars to repair around 500 kilometers of roads in the first phase of a broader government plan.It said the Roads and Employment Project was approved Monday to 'revamp the country's crumbling road sector.'The World Bank's Middle East director, said the project would "help Lebanon continue to offer basic services both to its citizens and to Syrian refugees in the country."Lebanon is home to some 1.2 million Syrian refugees, the equivalent of a quarter of its own population.For the AP, I'm SSF from the Rivet World Desk.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.458
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.006

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 head0.024
GPT teacher head0.300
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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