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Record W7020473417

Market review: Sic Transit Gloria Dux

2019· article· en· W7020473417 on OpenAlexaboutno aff

Bibliographic record

VenueHrčak Portal of scientific journals of Croatia (University Computing Centre) · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsConsolidation (business)Profit marginInitial public offeringCorporationWestern europeService (business)Quarter (Canadian coin)Mergers and acquisitions
DOInot available

Abstract

fetched live from OpenAlex

The beginningIn the third quarter of 1987 simultaneous announcements in Sweden and Switzerland made public the news that an agreement had been concluded which would see the merger of Asea AB and BBC Brown Boveri Ltd to form the new company ABB.Headquartered in Zurich, Switzerland each parent company held 50 percent of the new company and operations began on January 5, 1988.Over the next two years ABB acquired about 55 companies. Sic Transit Gloria Duxthe demand in emerging markets for new infrastructure drove expansion through internal growth acquisitions and majority joint ventures.In Asia, ABB now had 30,000 employees and 100 plants, engineering, service and marketing centres.ABB also completed the merger at Board level in 1996 with the integration of its parent companies' Boards into the ABB Group Board.Continuing with its expansion plans, ABB purchased Elsag Bailey, a process automation group, in 1997 which included Some of the major events are as follows:In 1990, ABB purchased Westinghouse's metering and control business Also, in the early 1990s, ABB purchased Combustion Engineering (C-E) 1994 saw ABB emerge from a twoyear consolidation phase to begin new volume and profit growth.The company concentrated on the fast-growing service markets in Western Europe and North America.Through the mid 1990' s

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)0.005
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: Review · Consensus signal: Review
Teacher disagreement score0.074
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0740.061

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 head0.015
GPT teacher head0.216
Teacher spread0.201 · 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
GenreReview

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
Published2019
Admission routes1
Has abstractyes

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