Molecular distillation of copaiba oleoresin—A clean process for diterpenes enrichment
Bibliographic record
Abstract
Abstract Copaiba oleoresin has sesquiterpenes and diterpenes with significant medicinal properties, including being antimicrobial, antiparasitic, and wound healing, among others. Thus, the objective of this work was to study the diterpene enrichment of the copaiba oleoresin from Copaifera officinalis via molecular distillation. Evaporator temperature (EVT) and feed flow rate ( Q ) were evaluated using an experimental design (2 2 with central point) considering the ratio of distillate and residue streams (DTR) as the response to optimize the residue recovery. EVT and Q were the main effects for diterpenes recovery, with the best experimental condition at 100°C (EVT) and 15 ml/min ( Q ) under 0.001 mbar, of which the residue stream had a diterpenes content of 99.25%. With the molecular distillation process, it was possible to add value to the copaiba streams, separating and purifying diterpenes with applicability in the biomedical and pharmaceutical industries since no solvent is used in this process (clean).
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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 | 0.000 |
| 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 | 0.000 |
| 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".