Combinations of Various Self-Consolidating Concrete Test Methods and Workability Responses
Bibliographic record
Abstract
Key workability characteristics of SCC can be described in terms of filling ability, passing ability, and resistance to segregation. These properties are typically characterized by data that relate to specific testing methods. In general, these methods include the components required for evaluating simultaneously filling ability, passing ability, and resistance to segregation, since these properties are rather interrelated. In this investigation, 33 SCC mixtures made with various mixture proportioning parameters, including maximum size and type of aggregate, type and content of binder, and w/cm were evaluated. Comparisons and correlations among various test results used in evaluating the workability responses obtained for these mixtures are established. This is done to highlight advantages and limitations of the various test methods that can be used to assess workability of SCC designated for precast, prestressed applications. Ranges of acceptance of the various test methods are also established.
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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 | 0.005 | 0.005 |
| 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) | 0.000 | 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".