Bibliographic record
Abstract
In a deal that would create a major new player in the lithium chemical industry, Allkem and Livent plan to merge in an all-stock transaction that values the combined company at $10.6 billion. Allkem and Livent currently produce a combined 60,000 metric tons (t) of lithium chemicals per year and aim to increase output to 248,000 t by 2027, which would make the merged company the third-largest lithium producer in the world, after Albemarle and SQM. In 2022, the companies had combined sales of $1.9 billion. Both firms have lithium mining projects in Argentina and Canada that are close to each other. Merging will allow them to share infrastructure and resources, they say, making their operations more efficient and moving projects forward faster. Allkem is also active in Australia. If the deal goes through, Livent CEO Paul Graves will lead the to-be-named company, and the headquarters will be in North
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.154 | 0.051 |
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".