Effect of aggregate on elasticity and strength properties of mortars under simulated exposure conditions.
Bibliographic record
Abstract
The purpose of the study was to investigate the relationships between properties of rock and the corresponding mortars under different environmental conditions as determined by compressive stress testing. The mortars were prepared with different type of aggregates but the same proportions of water, cement and aggregate. The rock aggregates were mostly carbonate rocks (limestone and dolomite). The mortar blocks were cured for 28 days. Three cores were drilled from each mortar block. The cores were first tested for water adsorption and absorption. Then, a series of compressive tests, up to 6.9 MPa (1000 psi), were performed on the mortar cores. The compressive tests were carried out under seven different environmental conditions: room (ambient) relative humidity (about 40% RE) and 98% RH, saturated in water, and saturated in 3% NaCl solution. All the tests were done at room temperatures (about 21°C) and freezing temperature (-20°C). The mortar data so obtained were then combined with the rock aggregate test results from previous studies, which included compressive tests (under same conditions), adsorption, absorption and magnesium sulphate loss. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 40-06, page: 1478. Thesis (M.Sc.)--University of Windsor (Canada), 2001.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".