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Record W4362582313 · doi:10.1021/cen-10111-buscon4

Cinven beats Ineos to buy MBCC Admixtures

2023· article· en· W4362582313 on OpenAlexaboutno aff
Alex Scott

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessCommerceCompetition (biology)Production (economics)Agricultural economicsEconomics

Abstract

fetched live from OpenAlex

Private equity firm Cinven has snatched a last-minute deal to buy MBCC Admixtures, part of BASF’s former construction chemical group, from the Swiss company Sika. As recently as Jan. 16, the chemical giant Ineos had announced that it was acquiring MBCC Admixtures . Since then, however, the UK’s Competition and Markets Authority (CMA) indicated that it had concerns that such an agreement would adversely affect the competitiveness of the UK construction chemical sector. Sika then turned to Cinven. MBCC Admixtures has annual sales of about $1 billion and over 1,600 staff at 35 production sites across Australia, Canada, Europe, New Zealand, and the US. Headquartered in Mannheim, Germany, the firm provides a broad range of products used in the construction industry, including materials that reduce carbon dioxide emissions in the production of concrete. Sika’s sale of MBCC Admixtures has itself been triggered by the CMA. If the business isn’t sold,

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: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.995

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.006

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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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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