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Record W2280196934 · doi:10.1080/10242694.2015.1123464

Special issue: defence inflation

2016· article· en· W2280196934 on OpenAlexaff
Keith Hartley, Binyam Solomon

Bibliographic record

VenueDefence and Peace Economics · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsCarleton UniversityDefence Research and Development Canada
Fundersnot available
KeywordsInflation (cosmology)Poison controlEconomicsForensic engineeringComputer securityEngineeringComputer scienceMedical emergencyMedicinePhysics

Abstract

fetched live from OpenAlex

Defence inflation is a recurring factor in determining defence spending. It is widely reported in official government publications and in the trade press, but remains relatively neglected by defenc...

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)0.003
metaresearch head score (Gemma)0.014
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.248
Threshold uncertainty score0.831

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.003
Science and technology studies0.0030.001
Scholarly communication0.0120.005
Open science0.0030.003
Research integrity0.0100.006
Insufficient payload (model declined to judge)0.2480.159

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 head0.029
GPT teacher head0.219
Teacher spread0.190 · 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
GenreEditorial

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

Citations6
Published2016
Admission routes1
Has abstractyes

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