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Record W4317798227 · doi:10.1021/cen-10103-buscon7

BASF takes huge write-off

2023· article· en· W4317798227 on OpenAlexaboutno aff
Alex Tullo

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Value (mathematics)EarningsBusinessFinanceEconomyEconomicsGeographyComputer science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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.

Opus teacher head0.020
GPT teacher head0.342
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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