Application of the CART Model to Classify the Perception of Young Canadian Teenagers on the Effect of Marijuana on Health
Bibliographic record
Abstract
The use of the illicit drug, marijuana has increased over years among young teenagers in different parts of the world and its harm on the health is generally well-known. This paper attempts to study the perception of young adolescents of 13-15 years old residing in Canada towards the danger of marijuana on health. To do so, a classification and regression tree (CART) has been applied on the data from the 2012 National Anti-Drug Strategy (NADS) Youth Advertising Recall and Tracking Survey. The decision tree has been applied and pruned on a training data set (70%) and evaluated on the testing data set (30%). The results show that the main indicators which impact on the perception of a teenager towards the harm marijuana has on health are the perceptions towards psilocybin (another illicit drug), the province in which the teenager lives and whether he/she has been ever offered drugs. The overall error rate on the testing data set based on the confusion matrix is less than 20% and the area under the ROC curve is relatively high showing that the model is accurate in classifying the perception of young teenagers on the health marijuana has on health.
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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 | 0.007 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".