A Simple DNA Extraction Method for Marijuana Samples Used in Amplified Fragment Length Polymorphism (AFLP) Analysis
Bibliographic record
Abstract
As a first step in developing a molecular method for the individualization of marijuana samples, we evaluated a plant DNA extraction kit. The QIAGEN plant DNeasy method uses a spin column format for recovery of DNA and is effective for obtaining high molecular weight DNA from leaf, flower (bud), and seed samples of marijuana. The average DNA yield was 125-500 ng per 100 milligrams of fresh plant tissue. The recovered DNA was of polymerase chain reaction (PCR) quality as measured by the ability to generate reproducible amplified fragment length polymorphism (AFLP) profiles. AFLP is a technique used to create a DNA profile for plant varieties and is being applied to marijuana samples by the authors to link growers and distributors of clonal material. The QIAGEN plant DNeasy method was simple, efficient, and reproducible for processing small quantities of marijuana into DNA.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".