World’s barite resources as critical raw material
Bibliographic record
Abstract
The relevance of the work is connected with the status of barite as a critical mineral raw material, as accepted in most industrialized countries. Purpose: to study the dynamics of commodity flows (production, import, export, consumption) of barite throughout the countries, its world prices, sources of barite raw materials and the prospects for its production and consumption. Methods: statistical, graphic, logical. Results. The production of barite raw materials from 0,3 Mt/year in 1920s grew intensively and reached 8.0–9.6 Mt/year in the 2010. Initially, both the mining and processing of barite raw materials industries were located directly in the USA, Germany, Britain, Italy, and France. These countries accounted for over 90% of world production and 80–95% of world consumption. In the 1950s, a sharp increase in the consumption of barite as a weighting agent for drilling fluids began. This led to an increase in its production in large oil and gas producing countries (the USA, the USSR, Mexico, Canada), export flows (from Morocco and other countries), and cessation of exports from Germany, Britain and France. The share of international trade in barite also increased from 0,3–0,5 Mt/year in the 1950s to 4.2–6.0 Mt/year (55–70% of his income) in the 2010s. The cumulative world production of barite between 1920–2020 is expected to be 550 Mt. World barite resources in deposits prepared for exploitation are estimated at 740 Mt. The group of critical countries importing barite raw materials (imports over 50%) represents 38.8% of the GDP of the world economy (USA, European Union, Germany, Italy, Saudi Arabia, Canada, Kuwait, Norway, Oman, Algeria, Malaysia, Indonesia, UAE, Azerbaijan, Argentina). The group of countries exporting barite raw materials includes 31.0% of the GDP of the world economy (India, Morocco, China, Kazakhstan, Turkey, Iran, Laos, Mexico, Pakistan, Bulgaria. A decrease in the criticality of barite raw material supply is possible as a result in reducing consumption (Japan, France, Italy and the Czech Republic), increasing world barite production with the commissioning of new deposits, given the significant prepared resources of this raw material in Iran, Kazakhstan and Pakistan, as well as the search for new barite deposits, including chemogenic marine bottom sediments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".