Trend 03/1995 - 12/2014. World Bank. Global Economic Monitor: Exports Merchandise, Customs, Current USD, Seasonally Adjusted | Country: Canada, 03/1995-12/2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 051-003-010.
Bibliographic record
Abstract
World Bank (2015). Global Economic Monitor: Exports Merchandise, Customs, Current USD, Seasonally Adjusted | Country: Canada, 03/1995-12/2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 051-003-010. Dataset: Reports exports of merchandise (goods), free on board (f.o.b.), in current millions of United States dollars, seasonally adjusted. Data reported in current prices are in the value of the currency for that particular year. The data are reported by country, for low-income and middle-income countries by geographic region (ie, Economic Reporting Entity), and by country income level. The Global Economic Monitor (GEM) dataset includes economic indicators on 196 countries. Data are provided where available by country, country group, and/or reporting entity. Statistics presented include interest rates, exchange rates, equity markets, bond spreads, consumer prices, Gross Domestic Product, industrial production, and merchandise trade.The World Bank obtains this data from its own databases, the International Monetary Fund and other sources. The Bank normalizes the data to the extent possible to support country-country comparisons. Data sources and years of coverage vary across indicators. Much of the data comes from the statistical systems of World Bank member countries. The quality of the data depends on how well these national systems perform. Errata announcements are posted periodically by the World Bank at http://data.worldbank.org/about/data-updates-errata. Category: International Relations and Trade Source: World Bank Founded in 1944 as a result of the Bretton Woods Conference, the World Bank is an independent specialized agency of the United Nations that provides financial and technical assistance to developing countries in order to foster economic growth and reduce poverty. Today, the World Bank Group comprises five institutions owned by 187 member countries: the International Bank for Reconstruction and Development (IBRD), which focuses on middle-income and creditworthy poor countries; the International Development Association (IDA), which focuses on least developed countries; the International Finance Corporation (IFC); the Multilateral Guarantee Agency (MIGA); and the International Centre for the Settlement of Investment Disputes (ICSID). http://www.worldbank.org/ Subject: Exports, Merchandise, International Trade
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.100 | 0.097 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".