Interaction between fine particles and colloidal gas aphrons (CGA)
Bibliographic record
Abstract
Interactions between fine particles (-10 µm) and colloidal gas aphrons (CGA) were predicted from zeta potential measurements, which were then compared to flotation experiments.CGAs, which are microbubbles coated and stabilized by a surfactant, were used as to selectively recover fine iron oxide or silica particles.Surfactant adsorption was measured by the changes in zeta potential as a function of surfactant addition.Using synthetic mineral (-10 µm) particles, four sets of recovery experiments were conducted using negatively charged CGA and positively charged CGA ( iron (III) oxide and sodium dodecylsulfate (SDS) CGA, silicon dioxide and SDS CGA, iron (III) oxide and hexadecyltrimethylammonium bromide (HTAB) CGA, and silicon dioxide and HTAB CGA).In addition, the recovery of natural fine mineral particles (hematite and quartz) was tested using an identical experiment setups.Both sets of synthetic particles and natural minerals showed positive correlations between recovery experiments and surfactant adsorption experiments.Therefore, high levels of particle recovery is related to good adsorption of surfactant onto the surface of particles, which is in agreement with electrostatic interactions of particles and CGA.Conversely, low levels of particle recovery is associated with poor
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".