Chemical Composition and Biological Activities of the Volatile Oils of Palisota hirsuta (Thunb) K. Schum and Trema orientalis (L) Blume
Bibliographic record
Abstract
Leaves of Palisota hirsuta (Thunb) K. Schum. and Trema orientalis (L) Blume. were collected from a farm land in Nigeria. The volatile oils were isolated using hydrodistillation and GC-MS method to determine their yield and composition. Antimicrobial activities of various oils obtained were also evaluated. Thirty-three (33) and thirty-seven (37) compounds were identified representing 98.9% and 99.4% of the entire constituents in the leaf oils of P. hirsuta and T. orientalis respectively. The main components of P. hirsuta oil were nonanal (19.6%), 1-Octen-3-ol (9.4%), hexenal (7.7%) and o-Cymene while those from T. orientalis were tetradecanal (33.3%), n-hexadecanoic acid (19.5%), farnesylacetone (5.6%) and linalool (4.3%). Both leaf oils displayed different activity against the tested microorganisms.
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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 | 0.000 | 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) | 0.001 | 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".