Bibliographic record
Abstract
According to London-based Oghma Partner, 2013 was a big year for global F&B mergers and acquisitions activity. Heading the list (by value) was Suntory Beverage & Food's purchase of GlaxoSmithKline's Lucozade and Ribena business for £1.4 billion, followed by the sale of Burton's Biscuit Company to Ontario Teachers' Pension Plan for £350 million and Distell's £160 million purchase of Scotland's Burn Stewart Distillers. The next two biggest deals, at £100 million each, were Coca-Cola's purchase of a 32 per cent share in Innocent Drinks and Investcorp's acquisition of Tyrrell's Potato Crisps. Analysts predict that interest in mergers and acquisitions should rise further in 2014 as the global economy grows stronger (although SA still is expected to face a constrained business environment).
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 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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.021 | 0.011 |
| Insufficient payload (model declined to judge) | 0.060 | 0.053 |
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".