Anheuser-Busch InBev reports Second Quarter and Half Year 2010 Results For important disclaimers please refer to page 3 HIGHLIGHTS
Bibliographic record
Abstract
and soft drink volumes up 5.5%. In HY10, total volumes increased 1.5%, with own beer volumes up 1.4 % and soft drink volumes up 3.9% Focus Brands: Our Focus Brand volumes grew 5.7 % in 2Q10 and 4.0 % in HY10, led by Budweiser internationally, Antarctica, Brahma and Skol in Brazil and Harbin in China Market share gains: In HY10, we gained or maintained market share in markets representing almost half of our total beer volumes Revenue growth: 2Q10 revenue rose 4.1%, or 1.5 % per hectoliter, and HY10 revenue grew 3.1%, or 1.3 % per hectoliter. On a constant geographic basis, growth in revenue per hl would have been 2.8 % for 2Q10 and 2.7 % for HY10 Cost of Sales: Cost of Sales (CoS) increased 2.9 % in 2Q10, and decreased 0.3 % per hl. In HY10, CoS increased 0.9%, and decreased 1.3 % per hl. On a constant geographic basis, CoS per hl would have increased 1.1 % in 2Q10 and 0.8 % in HY10 Sales and marketing: Sales and marketing investments grew 10.0 % in 2Q10 and 7.6 % in HY10, with increased support to our Focus Brands and global sponsoring activities before and during the FIFA World Cup partly offset by reductions in non-working money in North America
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.605 | 0.522 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".