MétaCan
Menu
Back to cohort
Record W167546701

CHANGES IN AGGREGATE PRODUCTION AND USE IN VICTORIA, BC

2003· article· en· W167546701 on OpenAlexaboutno aff
T S Coulter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsAggregate (composite)ConurbationPopulationEnvironmental scienceGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Development in the conurbation of Victoria, BC, on the southeast corner of Vancouver Island, has benefited from having many good quality sand and gravel pits in the immediate vicinity. Over the years, many of the pits have become depleted and, while undeveloped deposits of sand and gravel near Victoria still remain, these now cannot be accessed because of encroaching development and land-use zoning changes. The local demand for aggregates continues to increase as the population expands in the overall Capital Regional District-1 (CRD). The aggregate supply and demand in the CRD has been studied over the past 15 years and the changes in the types of materials and the sources of production have been observed. These studies show a major shift to aggregate production from sand and gravel pits to quarry sources, an increase in the use of recycled Portland cement concrete and asphalt concrete pavement in aggregates, and importation of increased volumes of aggregates from outside the CRD. This paper describes the trends in aggregate supply in the CRD and its implications for future aggregate production.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.191
Teacher spread0.179 · 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 designObservational
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

Citations1
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicMining and Resource ManagementFrench-language works237,207