English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

COMPASS is a longitudinal, prospective cohort study collecting data annuallyfrom students attending high school in jurisdictions across Canada. We aimed todiscover significant frequent/rare associations of behavioral factors amongCanadian adolescents related to cannabis use. We use a subset of COMPASSdataset which contains 18,761 records of students in grades 9 to 12 with 31selected features (attributes) involving various characteristics, from livinghabits to academic performance. We then used the Pattern Discovery andDisentanglement (PDD) algorithm that we have developed to detect strong andrare (yet statistically significant) associations from the dataset. PDD usedthe criteria derived from disentangled statistical spaces (known asRe-projected Adjusted-Standardized Residual Vector Spaces, notated as RARV). Itoutperformed methods using other criteria (i.e. support and confidence) popularas reported in the literature. Association results showed that PDD candiscover: i) a smaller set of succinct significant associations in clusters;ii) frequent and rare, yet significant, patterns supported by population healthrelevant study; iii) patterns from a dataset with extremely imbalanced groups(majority class: minority class = 88.3%: 11.7%).

Cohort Characteristics and Factors Associated with Cannabis Use among Adolescents in Canada Using Pattern Discovery and Disentanglement Method