New Mitigation Strategies for Cement Prehydration
Bibliographic record
Abstract
Portland cement has a limited shelf life because of the prehydration that can occur during storage. One approach to mitigating strength losses observed for concrete is to pretreat cement with a protective coating to slow the advance of prehydration. This study compared cement pretreatments with alkyl ketene dimer (AKD) wax and a combination of AKD + paraffin wax to a more traditional pretreatment approach using oleic acid. After exposing the treated cements to elevated temperature and humidity conditions, paste and mortar calorimetry tests showed improved resistance to prehydration reactions. The cements aged up to 12 weeks under the accelerated regime showed strength improvement for the mortars made with AKD and AKD + paraffin-treated cements relative to the mortars made with oleic acid-treated cement and mortars made with untreated cement. The wax can be added during clinker milling and additionally functions as a grinding aid.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 | 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 teacher head, 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".