Catching the Elusive Water-Cement Ratio Using Petrographic Methods—and Their Evaluation
Bibliographic record
Abstract
Abstract Petrographers use a variety of techniques for estimating the w/c and w/cm of hardened concrete. The estimates are routinely accepted by the concrete industry. Generally, four general methods are popular today: (1) water-droplet absorption; (2) scratch hardness; (3) combination of 12 or so microscopical and physical observations of the paste; and (4) methods where thin sections of concrete are impregnated with blue- or fluorescent-dyed epoxy. Sometimes combinations are used. There are few specific details in the literature for assessing the precision of the w/c using these methods except for the fluorescence technique, where there has been controversy about its claimed accuracy. The degree of interpretation of data from each method is based upon the comfort of petrographers in extending their expertise to provide that estimate. The deftness, skill, and experience of the petrographers will usually dictate their comfort zone. However, sometimes confounding that estimate is the existing concrete condition. The acceptability of the petrographic estimates depends on: (1) competency of the petrographer; (2) validity of the technique(s) used; (3) ability of the petrographer to qualify the techniques used; (4) the purpose(s) to which the data will be used; and (5) needs of those who either want to accept the estimates or debunk the estimates—for whatever reason.
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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 | 0.002 | 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 | 0.000 | 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".