Optimisation of metal extraction from chromium ore processing residue in New Jersey, USA
Bibliographic record
Abstract
The feasibility of extracting metals from chromium (Cr) ore processing residue (COPR) was investigated. COPR samples collected from four sites in New Jersey, USA (sites A, B, C and D) were mixed with 15% carbon by weight with different percentages of sand to neutralise the basic oxide in COPR and heated under a reducing environment to extract metals. At 15% and higher sand additions, a pool of melted metal was formed underneath the slag for some test batches. In this research, knowing the chemical composition of COPR and the depth of melt, the chemical engineering tools of phase and viscosity diagrams were used to compute the type and amounts of additives needed to optimise and compute the temperature and duration of melt to achieve maximum metal separations. With optimisation, as much as 30% by weight of metal was extracted from the initial mass of COPR collected from sites C and D when those melting mixtures contained 20% or more sand by weight. On average, the metal phase contained ∼90% of combined amounts of iron (Fe), chromium and titanium (Ti).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".