Method and apparatus for separating low density particles from feed slurries
Bibliographic record
Abstract
In a method and apparatus for separating low density particles from feed slurries, a bubbly mixture is formed in a downcomer (14) and issues into a mid region (12) in a chamber (1). An inverted reflux classifier is formed by parallel inclined plates (6) below the mid region allowing for efficient separation of low density particles which rise up to form a densely packed foam (16) in the top of the chamber, and denser particles which fall downwardly to an outlet (29). PCT/AU2011/000682, ARIPO Patent No. AP4561, Australian Patent No. 2011261162, Brazilian Application No. BR1120120305654, Canadian Patent No. 2801380, Chilean Patent No. 56.650, Chinese Patent No. ZL201180034985.4, Columbian Patent No. 35802, Eurasian Patent No. 034687, European Application No. 2576070, Hong Kong Application No. 13109545.6, Indonesian Patent No. 000051501, Indian Application No. 8/DELNP/2013, Mongolian Patent No. 3919, Mexican Patent No. 330600, New Zealand Patent No. 604253, OAPI Patent No. 16263, Peruvian Patent No. 8502, Ukrainian Patent No. 108237, US Application 13/701,668, ZA Application 2012/09575.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.080 |
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".