Characterization of the Effective Density for the Separation of Immersed Objects in the Gas–Solid Fluidized Bed Coal Beneficiator
Bibliographic record
Abstract
Effective density for the separation of immersed objects which determines the performance of coal dry beneficiation is of primary importance for Gas–Solid Fluidized Bed Coal Beneficiator (GSFBCB) applications. Of all factors affecting the effective density, fluidization hydrodynamics and properties of medium particles and immersed objects play the dominant roles. By correlating all available experimental data found in the literature, a general correlation has been developed for the first time to predict the effective density for immersed object separation in fluidized beds, ρ sep = 0.95 ρ bed + 1.88 ρ drag, where ρ bed is the fluidized bed density, and ρ drag is the effective bed density contributed by fluidization hydrodynamics. This correlation could accurately predict the effective density for various immersed objects in fluidized beds with single or binary particle systems in existing experimental results. With wide applicability and great accuracy, the proposed correlation not only provides an efficient way for the design and operation of the GSFBCB for coal dry beneficiation but also is applicable for iron and copper ore pretreatment, agricultural crop cleaning, municipal solid waste classification, etc.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".