Correlation analysis between chemical components and sensory quality of coffee
Bibliographic record
Abstract
In order to study the relationship between chemical composition and sensory quality of coffee,the content of protein,reducing sugar,chlorogenic acid,trigonelline,caffeine and pH value of coffee bean from seven different producing areas were tested and analyzed.The results of Pearson Linear Correlation Test showed that,the content of caffeine and trigonelline and sensory score was negatively related,with the correlation coefficient of 0.855 and 0.366,and the difference was significant.High sensory score was positively correlated to the loss amount of caffeine(r =0.897),trigonelline(r =0.848),chlorogenic acid(r =0.933) and reducing sugar(r=0.713) with a significant difference.However,as for the loss amount of protein,the linear dependence was not remarkable.Besides,an improvement of pH value was observed after roasting.The pH value of coffee from different roasting degrees and origins were similar.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".