TiZir reports titanium slag output decline in Q1, forecasts rising minsands prices
Bibliographic record
Abstract
Mineral sands producer TiZir has announced a 33% year-on-year drop in output in the first quarter of 2018. The Norway-based company attributed the fall to “an unscheduled maintenance outage of the pre-reduction kiln stemming from a gearbox failure.” The company produced 34,000 tonnes of titanium slag and sold 36,600 tonnes in the first quarter, compared with 50,700 tonnes and 62,100 tonnes respectively in the fourth quarter of 2017. At the company’s Grande Cote mineral sands operation (GCO) in Senegal, West Africa, a drop in finished goods production was created primarily by a reduction in ilmenite volumes. These fell to 104,104 tonnes in the first quarter of 2018 from 126,298 tonnes in the last quarter of 2017. Production of zircon in the first quarter declined slightly to 15,805 tonnes from 16,400 tonnes in the previous quarter, but sales increased to 17,906 tonnes from 17,614 tonnes in the same comparison.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.018 |
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".