Yielding Morphological Characteristics and Biochemical Analysis of “Karma lemon” Cannabis Producing Cannabinoids in Thessaloniki-Greece
Bibliographic record
Abstract
Cannabis has been widely used by humans over many centuries as a source of fiber, oil and for medicinal purposes. Its use was illicit in numerous countries, including Greece and Lebanon. “Karma Lemon”, one of the newest cannabis strain originated from Italy, is selected in this study to analyze its components using various techniques starting from the extraction, isolation and identification of cannabinoids using separatory compounds and NMR techniques as well as the main important morphological traits of this strain to be harvested at an appropriate time for medicinal uses in Greece and later on, in Lebanon. Thirty different samples were selected from the field of respected “Hemp Way Company” in Thessaloniki and studied for morphological traits. These were related to the length of the plant at harvest time (1.809 m) needed for the use of combines and the weight of inflorescence (213.5 g fresh and 40.8 g dry) for oil or seed production. Three samples of Karma Lemon cannabis strain inflorescence were analyzed at the Laboratory of Pharmacognosy, School of Pharmacy, in the Aristotle University of Thessaloniki in Greece, after proper extraction and isolation using ethanol and other separation compounds. TLC and NMR techniques were used to visualize and identify cannabinoids present after isolation. Cannabinoid acids, CBG, CBN, THC, CBD and other cannabinoids were identified and isolated.
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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 | 0.001 | 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) | 0.001 | 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".