Gas chromatography–mass spectrometry analysis of Alaska yellow-cedar extractive components.
Bibliographic record
Abstract
Alaska yellow-cedar (Cupressus nootkatensis) is a softwood tree species native to the Pacific coast of Canada and is known to contain various biologically active extractive components.Extractives are nonstructural chemical compounds found within wood that are primarily responsible for the durability of the tree itself and can, in some species, fend off attacks from microbes, insects, and other agents.Durability in wood often translates to biological activity in the human body, and some extractive compounds have already been identified as being biologically active.Extractives of Alaska yellow-cedar were separated using liquid-liquid fractionation and were identified using gas chromatography-mass spectroscopy (GC-MS).Vial B solvent mixture polarity separated 50% of the sample and had more compounds identified than the other fractions.The separated samples in vials F and G each had only one compound identified, and vial H had no compounds identified.Multiple compounds were identified in the other fractions that exhibit biological activity, such as carvacrol, nootkatone, α-cadinol, androsta-1,4,6-trien-3one,17-hydroxy-(17β), and falcarinol.Further investigation on the vials with one or less compounds will be analyzed using instrumentation with more sensitivity and resolving power to identified trace compounds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".