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Record W6957942635 · doi:10.6068/dp1753adf91db84

TREND: International Monetary Fund. Direction of Trade Statistics: Goods, Value of Imports, Free on board (FOB) | Country: Canada | Counterpart Country: JAPAN, 1948 - 2019. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 056-002-005

2020· other· en· W6957942635 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2020
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPhytochemistry and Biological Activities
Canadian institutionsnot available
Fundersnot available
KeywordsValue (mathematics)Balance of paymentsInternational financePaymentPort (circuit theory)Official statisticsExchange rateMonetary system

Abstract

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International Monetary Fund. Direction of Trade Statistics: Goods, Value of Imports, Free on board (FOB) | Country: Canada | Counterpart Country: JAPAN, 1948 - 2019. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 056-002-005 Dataset: Shows "free on board" (f.o.b.) imports for each country, by trading partner. Free on board measures freight including the delivery of goods on board a vessel at a port of origin (loading), at seller's expense. The buyer is responsible for the main carriage/freight, cargo insurance and other costs and risks. Note that this data series does not provide statistics for a World (International) total. Provides statistics on the value of merchandise exports and imports disaggregated according to a country’s trading partners. Reported data are supplemented by estimates when such data are not available or current. http://data.imf.org/?sk=9D6028D4-F14A-464C-A2F2-59B2CD424B85 Category: International Relations and Trade Subject: International Trade, Imports Source: International Monetary Fund Headquartered in Washington, DC, the International Monetary Fund (IMF) was conceived at a United Nations conference convened in Bretton Woods, New Hampshire, United States, in July 1944. The 44 governments represented at that conference sought to build a framework for economic cooperation that would avoid a repetition of the vicious circle of competitive devaluations that had contributed to the Great Depression of the 1930s. As of 2015, the IMF has 188 member countries. Its primary purpose is to ensure the stability of the international monetary system, specifically the system of exchange rates and international payments that enables countries (and their citizens) to transact with one other. This system is essential for promoting sustainable economic growth, increasing living standards, and reducing poverty. The Fund’s mandate has recently been clarified and updated to cover the full range of macroeconomic and financial sector issues that bear on global stability. The IMF is a specialized independent agency of the United Nations but has its own charter, governing structure, and finances. Its members are represented through a quota system broadly based on their relative size in the global economy. http://www.imf.org/

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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.351
Threshold uncertainty score0.705

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0100.034
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0960.143

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 head0.023
GPT teacher head0.229
Teacher spread0.206 · 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
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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