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Record W4283375839 · doi:10.1021/cen-10014-buscon4

Chemical companies start 2022 strong

2022· article· en· W4283375839 on OpenAlexaboutno aff
Alex Tullo

Bibliographic record

VenueC&EN Global Enterprise · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsnot available
Fundersnot available
KeywordsProfit marginQuarter (Canadian coin)Profitability indexEarningsBusinessNet incomeEconomicsFinanceMonetary economicsCommerceAgricultural economics

Abstract

fetched live from OpenAlex

First-quarter financial results are starting to come in from chemical makers, with Dow announcing its earnings and a few major German firms releasing preliminary figures. The companies are posting large increases in sales from a year earlier, but all have been laboring to maintain profitability in the wake of escalating energy and feedstock costs. Dow posted a 28% sales increase in the quarter versus the quarter a year earlier . Selling prices also increased 28%, while volumes climbed a more modest 3%. Net income, excluding unusual items, rose 70%. But profits at Dow’s largest business, packaging and specialty plastics, remained flat versus the year-earlier quarter , and the business’s before-tax profit margin fell from 20% to 16% as a consequence of rising energy costs. Profitability expanded in Dow’s intermediates and coating materials segments because of strong demand and higher selling prices. “We capitalized on end-market demand strength across the breadth

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.283
Threshold uncertainty score0.946

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0100.004
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.2830.204

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 head0.022
GPT teacher head0.240
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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