Elimination of tryptamines from green coffee by supercritical <scp>CO<sub>2</sub></scp> extraction
Bibliographic record
Abstract
Abstract Supercritical CO 2 (SC‐CO 2 ) extraction is commonly used to eliminate caffeine from coffee beans. In this work, the feasibility of tryptamine elimination is considered as a further objective of the process. SC‐CO 2 extraction process parameters (eg, pressure, CO 2 flow rate, water content) were studied to obtain tryptamine reduction, starting from those used in supercritical decaffeination. A good compromise, in terms of tryptamine residue in coffee beans, and process feasibility and selectivity, was found operating at 280 bar and 0.8 kg/h CO 2 , at a starting H 2 O content in coffee beans of 20% w/w. Using these process conditions, a tryptamine residue of 218 ppm (ppm) was measured in coffee beans after 18 hours of processing. A negligible effect on process selectivity and tryptamine yield was obtained by changing the CO 2 flow rate and the initial water content. However, working at an initial water content of 30% w/w and using wet CO 2 (CO 2 plus 3% w/w water), a tryptamine residue of 107 ppm in coffee beans was obtained, but industrial complexity and costs increased.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".