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Record W4402312112 · doi:10.21105/joss.06781

piar: Price Index Aggregation in R

2024· article· en· W4402312112 on OpenAlexfundno aff
Steve Martin

Bibliographic record

VenueThe Journal of Open Source Software · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsIndex (typography)MathematicsEconometricsStatisticsComputer scienceProgramming language

Abstract

fetched live from OpenAlex

The systematic inflation of prices for goods and services over time is a ubiquitous feature of modern economies.A price index is the main empirical tool to measure changes in prices over time, and consequently price indexes are a core macroeconomic statistic produced by national statistical agencies to measure and study inflation.Price indexes are often made with a two-step procedure-especially those coming from national statistical agencies-where period-over-period indexes are calculated for a large collection of well-defined goods and services at each point in time and aggregated according to a hierarchical structure (ILO et al., 2004; IMF et al., 2020).These aggregated indexes can then be chained together to form a collection of time series that give the evolution of prices in the economy with respect to a fixed point in time.

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)0.010
metaresearch head score (Gemma)0.092
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: Software · Consensus signal: none
Teacher disagreement score0.223
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.092
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.013
Science and technology studies0.0010.001
Scholarly communication0.0100.007
Open science0.0050.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2230.239

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 head0.024
GPT teacher head0.276
Teacher spread0.251 · 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
GenreSoftware

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
Published2024
Admission routes1
Has abstractyes

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