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Record W2503430319 · doi:10.1002/9781119198161.app1

ISO Currencies Pairs

2012· other· en· W2503430319 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsFocus (optics)Library scienceComputer sciencePhysics

Abstract

fetched live from OpenAlex

A ISO Currencies PairsT his is a list of global currencies and the three-character currency codes that we have found are generally used to represent them.Often, but not always, this code is the same as the ISO 4217 standard.(The ISO, or International Organization for Standardization, is a worldwide federation of national standards.)In most cases, the currency code is composed of the country's two-character internet country code plus an extra character to denote the currency unit.For example, the code for Canadian Dollars is simply Canada's two-character internet country code ("CA") plus a one-character currency designator ("D").We have endeavored to list the codes that, in our experience, are actually in general industry use to represent the currencies.Currency names are given in the plural form.This list does not contain obsolete Euro-zone currencies.

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)0.006
metaresearch head score (Gemma)0.026
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: Other
Teacher disagreement score0.171
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.014
Science and technology studies0.0030.001
Scholarly communication0.0110.013
Open science0.0030.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1710.166

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 head0.034
GPT teacher head0.229
Teacher spread0.195 · 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
Published2012
Admission routes1
Has abstractyes

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