Ilustración y Pre-romanticismo canarios: una obra del Doctoral Garaciliano Afonso (1775-1861)
Bibliographic record
Abstract
There is some evidence that cannabis use is associated with lower cognitive performance and symptoms of attention-deficit/hyperactivity disorder (ADHD), but the existing literature is relatively inconsistent, potentially due to small samples in previous studies. Using a dimensional design, the current study examined cannabis use severity and age of first cannabis use in relation to neurocognitive performance and ADHD symptoms in a large sample of community adults (<i>N</i> = 1,008, <i>M</i><sub>age</sub> = 38.49, 56.0% female). Participants were assessed for cannabis involvement, neurocognitive performance, and ADHD symptoms. Dimensional relationships were investigated using multiple hierarchical regressions. Using a covariate model of age, income, sex, alcohol use, and tobacco use, severity of cannabis involvement was significantly associated with greater endorsement of both hyperactive-impulsive and inattentive ADHD symptoms but not with any other cognitive measures in the full sample. Exploratory analyses found greater cannabis use severity was associated with digit span forward and hyperactive ADHD symptoms in young adults (<i>n</i> = 371) and was associated with greater delay discounting, hyperactive, and impulsive ADHD symptoms in high-risk cannabis users (<i>n</i> = 161). Age of first cannabis use was not significantly associated with any neurocognitive variables or ADHD symptomatology in all analyses. The current findings provide evidence of a link between current cannabis misuse and both hyperactive and inattentive ADHD symptoms in general, and possible links to attention and impulsive delay discounting in subgroups of cannabis users, but no associations in other cognitive domains or implication of earlier initiation of cannabis use in relation to cognitive performance or ADHD. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.000 | 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 | 0.001 | 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) | 0.004 | 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".