Experience with end-result specifications for granular base aggregates in Ontario
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".