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Record W4408289811 · doi:10.1021/cen-10306-buscon6

Business briefing

2025· article· en· W4408289811 on OpenAlexaboutno aff

Bibliographic record

VenueC&EN Global Enterprise · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessProcess managementComputer science

Abstract

fetched live from OpenAlex

Borealis, Borouge, and Nova to combine Abu Dhabi National Oil Company (ADNOC) and the Austrian refiner OMV are combining their petrochemical holdings to form Borouge Group International, which will be the fourth-largest polyolefins producer in the world, with 13.6 million metric tons of capacity. The new firm will merge European chemical maker Borealis, which is owned 75% by OMV and 25% by ADNOC, with Borouge, a United Arab Emirates polyolefins maker owned by 36% by Borealis and 54% by ADNOC. In addition, ADNOC will buy Canada’s Nova Chemicals for $13.4 billion, including debt, from the Abu Dhabi sovereign wealth fund Mubadala Investment. Nova will be contributed to the combined company when it is formed in 2026. The new firm will also include Borouge 4, a $7.5 billion ethylene cracker complex under construction in Abu Dhabi. Borealis, Borouge, and Nova have a total of about $17 billion in annual sales, based

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.368
Threshold uncertainty score0.901

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0070.004
Open science0.0020.002
Research integrity0.0110.007
Insufficient payload (model declined to judge)0.3680.325

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 head0.005
GPT teacher head0.305
Teacher spread0.300 · 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.

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
Published2025
Admission routes1
Has abstractyes

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