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Record W2212802402

Designing New Zealand's New Banknote Series

2014· article· en· W2212802402 on OpenAlexaboutno aff
Kristin Langwasser

Bibliographic record

VenueReserve Bank of New Zealand Bulletin · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsBanknoteCall for bidsVariety (cybernetics)Process (computing)BusinessComputer scienceCommerceIndustrial organizationEconomicsMarketingMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Earlier this year the Reserve Bank of New Zealand selected the designs for the next series of New Zealand banknotes, and published them in November. This article takes the reader through the process of designing the next banknote series, including the often intricate challenges of ensuring that those banknotes meet a variety of aesthetic, cultural and functional requirements. To best achieve the design goals, the Reserve Bank uses an open tender process. The tenders for the design and the printing were won by the Canadian Banknote Company Ltd. (CBN).

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)0.020
metaresearch head score (Gemma)0.038
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 score0.077
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0100.007
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0770.023

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 head0.031
GPT teacher head0.216
Teacher spread0.186 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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