Chemical makers see cause for optimism in financial results
Bibliographic record
Abstract
For the chemical industry, the third quarter of 2025 may prove to have been an inflection point. It was a difficult period for most chemical makers, but not without signs of better times ahead.In its earnings announcement, BASF, the world’s largest chemical maker, heralded that its results, which included a 3.2% decline in sales and a 62.5% increase in earnings, beatmarket expectations. In prepared remarks, CEO Markus Kamieth blames the sales decline on lower prices and currency headwinds. In a positive sign for the firm, sales volumes increased in its surface technology, chemical, and materials segments.“In the third quarter of 2025, market dynamics continued to be challenging: Upstream margins were still under pressure, and customer buying behavior in almost all industries and regions remained cautious,” Kamieth says.Celanese CEO Scott Richardson echoed the sentiment in prepared remarks about the quarter. The company’s engineering polymers business didn’t do as well as it had expected. Auto production, an important market for that business, slipped 2% from the preceding quarter. “End markets remain cautious amid lingering geopolitical risks,” Richardson says. Overall, Celanese’s sales were down 8.6%, and earnings dropped 44.4% from the year-earlier period. The Germany specialty chemical firm Evonik Industries had a rough quarter, with declines across its entire business. In total, the company posted an 11.5% drop in sales and a 52.8% drop in earnings. "The anticipated recovery in September failed to materialize,” Evonik CEO Christian Kullmann says in the third-quarter earnings report. “In the short term, this is painful. But longer
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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 | 0.025 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.014 | 0.021 |
| Insufficient payload (model declined to judge) | 0.053 | 0.017 |
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".