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Record W2065541037 · doi:10.1080/1941658x.2013.843423

Feasibility of Budget for Acquisition of Two Joint Support Ships

2013· article· en· W2065541037 on OpenAlexaffabout
Erin Barkel, Tolga Raymond Yalkin

Bibliographic record

VenueJournal of Cost Analysis and Parametrics · 2013
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsUniversity of OttawaCarleton UniversityLibrary of Parliament
Fundersnot available
KeywordsJoint (building)Computer scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

The mandate of the Parliamentary Budget Officer is to provide independent analysis to Parliament on the state of the nation's finances, the government's estimates, and trends in the Canadian economy, and, upon request from a committee or parliamentarian, to estimate the financial cost of any proposal for matters over which Parliament has jurisdiction. The PBO received requests from the Member from St John's East and the Member from Scarborough-Guildwood to undertake an independent cost assessment of the Joint Support Ship project. This report assesses the feasibility of replacing Canada's current Auxiliary Oiler Replenishment ships with two Joint Support Ships within the allocated funding envelope. The cost estimates and observations presented in this report represent a preliminary set of data for discussion and may change subject to the provision of detailed financial and non-financial data to the Parliamentary Budget Officer by the Department of National Defence, Public Works, and Government Services Canada, and the shipyards. The cost estimates included reflect a point-in-time set of observations based on limited and high-level data obtained from a variety of sources. These high-level cost estimates and observations are neither to be viewed as conclusions in relation to the policy merits of the legislation nor as a view to future costs.

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)0.017
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0340.003

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 head0.298
Teacher spread0.264 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations3
Published2013
Admission routes2
Has abstractyes

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