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Record W7024855467

Summaries of economic data: Central African Republic

2018· report· en· W7024855467 on OpenAlexaboutno aff

Bibliographic record

VenueEconomic Commission for Africa Knowledge Repository (Economic Commission for Africa) · 2018
Typereport
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsnot available
Fundersnot available
KeywordsCensusPopulationAgricultureManufacturingQuarter (Canadian coin)Statistical analysis
DOInot available

Abstract

fetched live from OpenAlex

Summaries of economic data the case of Central African Republic 1975. The 1970 Statistical Annual shows a population from the 1968 census of 2, 255,536. If the 1968 Census is accurate the 1972 population would be about 2, 5001 000 and that for 1973 about 2,555,000. With only very-limited information it is difficult to comment on the economic situation of the CAR in 1974. In 1974 import prices rose sharply and reports indicate increases of about 25 per cent in other Central and West African countries. Thus, imports in 1974 could have cost some 17 billion CFA francs. The existing industries serve the limited markets of the CAR and Southern Chad; some establishments process agricultural products for export and some small portion of the diamonds minded is also processed. One of the major objectives is to create 3,000 new jobs by 1975 adding to the 7,000 employees in 1970, Turnover in manufacturing industry is scheduled to increase from 10.7 billion francs CFA in 1970 to 20,9 billion in 1975.

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)0.012
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 score0.116
Threshold uncertainty score0.387

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0120.028
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1160.080

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 head0.081
GPT teacher head0.320
Teacher spread0.239 · 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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