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Record W1993439594 · doi:10.1139/l07-033

Experience with end-result specifications for granular base aggregates in Ontario

2007· article· en· W1993439594 on OpenAlexvenueaboutno aff
Chris Rogers, Stephen Senior

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsQuality assuranceSubbaseAcceptance testingGrading (engineering)Statistical process controlAggregate (composite)Christian ministryQuality (philosophy)Acceptance samplingComputer scienceEngineeringStatisticsOperations managementMathematicsProcess (computing)Civil engineeringSample size determinationMaterials science

Abstract

fetched live from OpenAlex

In 1982, the Ontario Ministry of Transportation (MTO) introduced end-result specifications (ERS) for the acceptance of granular base and subbase aggregates with respect to lot-by-lot statistical testing for grading and percentage of crushed particles. Under ERS, the mean and range of four test results (sublots) were used to determine the payment for specific production quantities (lots). Quality assurance (QA) sampling and testing were conducted at the aggregate source by the MTO. Materials within a lot that were, on average, marginally outside the specification limits or exhibited a wide range would be paid at a reduced contract price. Materials significantly exceeding these requirements would be rejected. In 1997, MTO introduced quality control (QC) requirements that made the contractor responsible for sampling and testing at the source. Quality assurance testing was based on a reduced number of samples taken from materials delivered to the worksite. Price adjustments, if any, were determined solely on QA test results (subject to a referee process). This paper describes in detail the steps taken to introduce these various ERS schemes. Acceptance for granular base materials at full price in 2002 has not changed significantly from 1994 and earlier years; the quantity of rejected materials has also not changed significantly over the years. It is concluded that the introduction of contractor QC testing has not significantly improved the quality of materials supplied, but neither has it had a detrimental effect.Key words: aggregate, construction, end-result specification, granular base, pavement, quality assurance, quality control, statistics, testing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.930
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.211
Teacher spread0.185 · 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 teacher head, 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

Citations1
Published2007
Admission routes2
Has abstractyes

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