Bibliographic record
Abstract
This paper describes the steps taken by the Ontario Ministry of Transportation (MTO) to improve high performance concrete (HPC), particularly for use in bridge decks. After some initial trial and demonstration projects, MTO expanded the use of HPC on its contracts and new end-result specifications were developed. HPC was defined as having a minimum specified 28-day strength of at least 50 MPa; requiring silica fume and allowing other supplementary cementing; and having a specified rapid chloride permeability at 28 days of 1000 coulombs or less. Air void parameter requirements for hardened concrete were also specified. An earlier requirement for a minimum cement content was removed, although there are some restrictions on the type of cement that must be used. To ensure that these standards are met, contractors are responsible for the sampling and testing of fresh and hardened concrete. The MTO requires extended wet curing and fog misting during concrete placement to minimize cracking. Despite some initial resistance from contractors and MTO field staff, this curing procedure has been adopted by the Canadian Standards Association. The MTO specification has proved to be workable and it is anticipated that use of HPC will gradually be increased by the MTO. As contractors and suppliers become more familiar with HPC and the performance characteristics of their mixtures, they are expected to provide more customization of mixture proportions.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".