Development and Characterization of Cementing Composites with Blast Furnace Slag Replacement
Bibliographic record
Abstract
In this work, they were produced and characterized cementing composites made with blast furnace slag replacement, for their use in the construction of oil wells. To this, slurries were prepared with a replacement of 20 and 30% slag, as well as a slurry with 100 % slag and a slurry with 100% H-cement were prepared. Starting materials were characterized by chemical analysis, X-ray diffraction and Fourier Transformed Infra Red. Slurries also were activated with sodium silicate in order to study theirs hydration kinetics, driving by isothermal calorimetry. These studies were complemented by the preparation of specimens of 4 X 4 X 16 cm to which they determine its compressive and bending strength during 2 and 28 days of curing. From the results it can be concluded that it was obtained a product that can be effectively used in the construction of oil wells.
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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 | 0.001 | 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".