A new approach to analyzing the type of moisture inside the filter cake of hematite concentrate
Bibliographic record
Abstract
Filters are widely used for dewatering in the mining industry. In general, different parameters affect vacuum filtration, such as solid percentage, vacuum level, particle size distribution, filter cloth, and chemical additives. These parameters can influence filtration properties such as cake moisture, throughput, and filter cloth lifetime. Moisture and throughput usually are used to determine the quality of filtration. In this study, new variables were used to express the filtration and characteristics of filter cake at a microscopic scale. The quality of the filter cake can be precociously analyzed using the void fraction and density of the filter cake. The present study aimed to propose some new variables to properly analyze the filtration process, improve the filtration rate, and decrease the cake moisture of Gol-E Gohar iron ore concentrate. In this regard, a series of filtration experiments were implemented using laboratory-scale bottom top-feed vacuum filters. The results showed that an increase in the solid percentage decreased the void fraction from 0.45 to 0.40 and increased cake density from 0.30 to 0.33 gr.cm-3, respectively. Increasing the particle size increased the void fraction from 0.415 to 0.43. Furthermore, the type of structural or capillary moisture of the filter cake could be determined using a void fraction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".