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Record W4385954795 · doi:10.3389/frym.2023.898445

Cannabis Use and the Developing Brain: Highs and Lows

2023· article· en· W4385954795 on OpenAlex
Yasmin L. Hurd, Jacqueline‐Marie N. Ferland, Yoko Nomura, Leslie A. Hulvershorn, Kevin M. Gray, Christian Thurstone

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers for Young Minds · 2023
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
FundersNational Institute on Drug AbuseQueens College, City University of New YorkUniversity of British ColumbiaChild Mind InstituteIcahn School of Medicine at Mount SinaiNational Academy of MedicineStavros Niarchos FoundationSchool of Medicine, Indiana UniversityCity University of New York
KeywordsCannabisEffects of cannabisBrain developmentPsychologyDevelopmental psychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

Although cannabis is a naturally occurring plant with a long history of use by humans, the chemicals it contains, called cannabinoids, can act on the human body in many ways. Use of cannabis during important periods of development, such as during pregnancy and adolescence, can have a long-lasting impact on the way the brain forms and develops its systems to control emotions and other functions. This article gives an overview of some of the effects of cannabinoids on the developing brain, before birth and as teenagers, and provides information about how young people can prevent or minimize the negative effects of cannabis on their brains.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.576
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.283
Teacher spread0.261 · 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