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Record W6966552588 · doi:10.4224/20377194

MIIP report: survey on municipal infrastructure assets

2004· report· en· W6966552588 on OpenAlexfundvenueaboutno aff

Bibliographic record

VenueNPARC · 2004
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
FundersMinistère de la Défense Nationale
KeywordsDeliverableAsset (computer security)Asset managementInvestment (military)Government (linguistics)Local governmentStrategic planning

Abstract

fetched live from OpenAlex

Municipal Infrastructure Investment Planning (MIIP) is a three-year project investigating decision support tools for strategic asset management (http://www.nrc-cnrc.gc.ca/eng/projects/irc/municipal-infrastructure.html). A defined deliverable for the project is a survey and report on existing levels of maintenance within the participating organizations and within Canadian municipalities. More specifically, the survey should validate the 2% to 4% 'Level of Investment' recommended by some government agencies (NRC US, 1994, 1996). This report addresses these project needs by investigating: (1) the actual and sustainable 'Level of Investment' expenditures for maintenance of municipal infrastructure; (2) the extent of asset management techniques in practice today, and (3) the state of Canada's municipal infrastructure assets. This report presents the results of a survey sent to 545 municipalities across Canada and presents and discusses the responses from 67 Canadian municipal infrastructure asset managers. Included in the number were responses from the federal departments, municipalities and regional municipalities participating in the MIIP project.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.004

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 head0.057
GPT teacher head0.341
Teacher spread0.284 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations5
Published2004
Admission routes3
Has abstractyes

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