Bibliographic record
Abstract
The vast majority of potash is found in Canada and Russia, which hold potash reserves of 4.4bn and 3.3bn tonnes respectively, of the world's 9.5bn tonnes total, according to the US Geological Survey (USGS). Figures from Russian potash producer, Uralkali, indicate that the oldest reserves in Russia were formed between 275m and 290m years ago, while Canadian deposits formed around 370m years ago under the earth's surface. Deposits in the UK, Germany and Brazil formed underground between 250m and 120m years ago. In its 2013 full year financial results, released in February 2014, PotashCorp. said that challenging fertiliser market conditions impacted our performance. In November 2013, Mosaic's CEO, Jim Prokopanko referred to the company's weak results caused by challenges in the environment in which we operate, while Uralkali's head of sales and marketing, Oleg Petrov, described potash demand as being in prolonged, steady decline following the demand highs of 2011. Whichever way one looks at it, 2013 was a difficult year for the potash industry as demand dropped, buyers held off from purchases and investors lost confidence. Several potash juniors though, such as ASX-listed Elemental Minerals developing the Sintoukola potash project in ROC, West Africa, have chosen to invest in the region. However, where Elemental plans to target South America with its potash, saying that the African market isn't there yet, other companies like Allana Potash anticipate that Africa will become a major power house with investment from the Middle East, China and Russia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.065 | 0.013 |
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".