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Record W6891557867 · doi:10.48321/d1389a37bf

How has the use of Cannabis affected the Brains of Adolescents from Grades 7-12

2024· other· en· W6891557867 on OpenAlexaffabout

Bibliographic record

VenueCalifornia Digital Library · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsLethbridge College
Fundersnot available
KeywordsAffect (linguistics)CannabisLegalizationEffects of cannabisBrain development

Abstract

fetched live from OpenAlex

Due to the legalization of Cannabis in Canada adolescents risk using it too early and affecting their brain development early on. Adolescents from grades 7-12, both male and female, can be affected differently. Using existing data from previous research can show us if cannabis use in adolescents can affect their brain development. Using different methods such as existing data, survey research, and field research can give us an excellent example of how often children are using Cannabis. Where are they getting it from, when did they start using Cannabis, and if the adolescent using Cannabis or not? The expected results of this research should show us that Cannabis is profoundly affecting brain development, making children react slower, not retain information, and not be as attentive as someone who is not using Cannabis. Some implications from this research could positively affect adolescent brain development, for example, adolescents paying more attention in class.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.036
GPT teacher head0.203
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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