Cobalt—Styles of deposits and the search for primary deposits
Bibliographic record
Abstract
Cobalt (Co) is a potentially critical mineral. The vast majority of cobalt is a byproduct of copper and (or) nickel production. Cobalt is increasingly used in magnets and rechargeable batteries. More than 50 percent of primary cobalt production is from the Central African Copperbelt. The Central African Copperbelt is the only sedimentary rock-hosted stratiform copper district that contains significant cobalt. Its presence may indicate significant mafic-ultramafic rocks in the local basement. The balance of primary cobalt production is from magmatic nickel-copper and nickel laterite deposits. Cobalt is present in several carbonatehosted lead-zinc and copper districts. It is also variably present in Besshi-type volcanogenic massive sulfide and siliciclastic sedimentary rock-hosted deposits in back arc and rift environments associated with mafic-ultramafic rocks. Metasedimentary cobalt-copper-gold deposits (such as Blackbird, Idaho), iron oxide-copper-gold deposits, and the five-element vein deposits (such as Cobalt, Ontario) contain different amounts of cobalt. None of these deposit types show direct links to mafic-ultramafic rocks; the deposits may result from crustal-scale hydrothermal systems capable of leaching and transporting cobalt from great depths. Hydrothermal deposits associated with ultramafic rocks, typified by the Bou Azzer district of Morocco, represent another type of primary cobalt deposit.
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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 | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".