Flocculation of precipitated calcium carbonate (PCC) by cationic tapioca starch with different charge densities. II: Population balance modeling
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Bibliographic record
Abstract
A population balance model to describe the flocculation of PCC by two cationic tapioca starches is presented. The model takes into account aggregation, floc breakage and floc restructure. Floc strength as indicated by energy dissipation rate was also evaluated. It was found that the high charge density starch relates to lower collision efficiency, lower restructure rate and higher floc strength (higher energy dissipation rate) compared to the case with the low charge density starch. Lower energy dissipation rate was needed to break the flocs at higher temperature for both starches. On the other hand, the high charge starch was more likely to be negatively affected by the background electrolyte NaCl. The collision efficiency decreased with the increase of the shear rate for both starches. The difference of charge, starch morphology on PCC surface and the charge suppression effect were employed to interpret the results.
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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 | 0.000 | 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 it