Heavy and Light Beer: A Carbon Isotope Approach To Detect C<sub>4</sub> Carbon in Beers of Different Origins, Styles, and Prices
Bibliographic record
Abstract
The carbon isotope ratios (delta(13)C) of 160 beers from around the world ranged from -27.3 to -14.9 per thousand, primarily due to variation in the percentage of C(3) or C(4) plant carbon in the final product. Thirty-one percent of beers had a carbon signature of C(3) plants (barley, rice, etc.), whereas the remaining 69% contained some C(3)-C(4) mixture (mean of mixtures, 39 +/- 11% C(4) carbon). Use of C(4) carbon (corn, cane sugar, etc.) was not confined to beers from any particular region (Pacific Rim, Mexico, Brazil, Europe, Canada, and the United States). However, the delta(13)C of European beers indicated mostly C(3) plant carbon. In contrast, U.S. and Canadian beers contained either only C(3) or C(3)-C(4) mixtures; Brazilian, Mexican, and Pacific Rim beers were mostly C(3)-C(4) mixtures. Among different lagers, U.S.-style lagers generally contained more C(4) carbon than did imported pilsners. Among different ales, those brewed by large high-production breweries contained significant proportions of C(4) carbon, while C(4) carbon was not detected in microbrewery or home-brew ales. Furthermore, inexpensive beers generally contained more C(4) carbon than expensive beers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".