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Record W4367609767 · doi:10.1021/cen-10114-buscon1

Dow’s first quarter comes in at a loss

2023· article· en· W4367609767 on OpenAlexaboutno aff
Alex Tullo

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)EarningsEconomicsBusinessFinanceHistory

Abstract

fetched live from OpenAlex

In the first major earnings announcement of 2023, Dow has posted a loss for the first quarter—an indication that the weak global economy, particularly in Europe, has created tough conditions for the chemical industry. Dow’s sales for the quarter were $11.9 billion, a 22% decline from the first quarter of 2022. The company posted a net loss of $73 million, compared with profits of nearly $1.6 billion in the year-earlier quarter. “Declines in all operating segments were driven by continued soft global macroeconomic activity,” Dow CEO Jim Fitterling said in a conference call with analysts. The results are in line with the expectations of BASF and Covestro, both of which recently disclosed estimates for the quarter. Blaming low production volumes, BASF expects sales in the quarter to drop by 13%. Covestro forecasts a 20% drop. Dow notes some positives, however. Sales were flat versus the fourth quarter of 2022, which

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.012
GPT teacher head0.288
Teacher spread0.276 · 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 designObservational
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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