Physico-Chemical Indices, Iso-alpha-Acid, Phenolic Contents and Antioxidant Activity of Commercial Beers
Bibliographic record
Abstract
The effects of brewing style on physicochemical indices, iso-a-acids and antioxidant contents of commercial beers were investigated. A great variability was highlighted for all the considered parameters (sugar and alcohol contents, density, pH, titratable acidity, iso-a-acids, phenolic content, antioxidant activity). The beers having the highest iso-a-acids contents were Guinness Special Export Stout (which also showed the highest phenolic content), Chimay Pères Trappistes Triple, and Greene King IPA whereas the lowest values were detected in Cuveè De Ranke, Heineken Premium Quality Lager, and Riedenburger Brauhaus gluten free. The latter also had the lowest phenolic concentration. The antioxidant activity values strictly correlated with the total phenolic content but not with the iso-?-acid amount. The Principal Component Analysis failed in distinguishing beers based on their declared type/styles. This was a predictable result since the beer styles don’t represent a compositional classification but they are rather used to indicate commercial types.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".