Bibliographic record
Abstract
In a reversal of a long-held industry practice, Corteva Agriscience plans to split its crop protection and seeds businesses into two separate companies next year.“We did not make this decision quickly or take it lightly,” Corteva CEO Chuck Magro said on a conference call with investors Oct. 1.The crop protection chemical business will continue to bear the Corteva name. The company projects that the unit will generate $7.8 billion in sales this year, 44% of its total. About half of its chemical sales come from herbicides and a quarter from insecticides. The crop protection business also has a growing presence in biologicals, which represent about 6% of its sales.The planned seed company, temporarily dubbed SpinCo, is home to the Pioneer brand and is expected to post $9.9 billion in sales this year. It is the North American leader in corn and soy and holds a number 2 position in cotton and canola.Magro will lead SpinCo. Corteva chair Greg Page will assume that role for Corteva after the separation.Corteva itself was established as part of the 2017 merger of Dow and DuPont, which combined the seed and crop protection businesses of the two big chemical companies. Corteva spun off on its own in 2019.Corteva’s split would buck industry norms. Agricultural peers such as Bayer, Syngenta, and BASF have both seed and crop protection chemical businesses and often pair certain chemicals and seeds as complete systems for farmers.But during the conference call, Magro said Corteva is outgrowing that model and that to
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.081 | 0.043 |
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".