Mixing strategy effect on dispersion of amine during reagent production for flotation applications
Bibliographic record
Abstract
Mixing and dispersion strategies for the inline production of amine flotation reagents is explored for 2.54 cm and 5.08 cm process lines and flow rates comparable to current commercial production systems. Through video analysis of injection into a clear pipe, the dispersion effectiveness was visualized and quantified as a variability intensity, and compared for natural‐stream turbulence, orifice‐plate and structured static mixing elements. The results suggest that a single point of energy dissipation was more effective in dispersing the injected amine, with the orifice plates consistently yielding fully‐dispersed reagent solutions. The results suggest that while a structured mixing device with 6 elements did improve dispersion relative to an empty pipe, more mixing elements or a smaller characteristic length (i.e. 2.54 cm mixer) would be better suited to this specific application.
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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 | 0.000 | 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".