Bibliographic record
Abstract
Some important uses of lithium are introduced, and the present status of lithium resource exploitation is analyzed. Lithium plays a unique role in atomic energy industry, so called high energy metal, and it promotes the energy industry, especially the development of battery technology, and is worthy of the name: the power metal and the metal promoting the world forward. With the development of technology, the conventional status of the global lithium industries and the market distributions have greatly changed. The advanced technology of extracting lithium from salt lake brine has broken the equilibrium lasted for half a century in lithium resource distribution and production. Australia, Russia, Canada and Zimbabwe, as large countries of hard rock lithium ores, will gradually lost the predominant position in lithium resources and lithium compound supplies worldwide. Chile, China, Argentina and Bolivia will be the remaining large countries with lithium resources. Lithium products from the salt lake industries are appropriate for the demand of the present knowledge economic age, and have good market prospect. In China, great progress has been made in technology of lithium salt lake brine operation. As one of the Western High-tech Industrialization Demonstration Projects, a plant of yearly output of 3000 tons lithium carbonate will go into production in June, 2005.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".