Bibliographic record
Abstract
BASF has taken a massive write-off of assets—$5.8 billion in the fourth quarter —for Wintershall Dea as the oil and gas affiliate exits completely from its Russian operations. The write-down includes the value of Wintershall Dea’s stake in the Nord Stream pipeline from Russia to Germany. BASF has taken a total of $7.8 billion in write-offs in 2022 related to Wintershall Dea, in which it owns a 73% interest . “Continuing to operate in Russia is not tenable. Russia’s war of aggression in Ukraine is incompatible with our values and has destroyed co-operation between Russia and Europe,” Wintershall Dea CEO Mario Mehren says in a statement. He also accuses Russia of expropriating Wintershall Dea’s joint ventures in the country. In its preannouncement of 2022 earnings, BASF says it expects a loss of $1.5 billion for the year, primarily because of the write-down. It earned nearly $6.0 billion in 2021 .
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.164 | 0.078 |
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".