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Record W3027151919 · doi:10.2147/ahmt.s254264

<p>Children and Youth Who Use Cannabis for Pain Relief: Benefits, Risks, and Perceptions</p>

2020· article· en· W3027151919 on OpenAlexaff
Julia Woo, Emma A. van Reekum, Tea Rosic, Zainab Samaan

Bibliographic record

VenueAdolescent Health Medicine and Therapeutics · 2020
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsCannabisMedical cannabisPsychiatryObservational studyPsychosisMedicineDepression (economics)AddictionPsychologyClinical psychology

Abstract

fetched live from OpenAlex

We provide up-to-date perspectives on the benefits and risks of medical cannabis for pain management in children and youth. To date, only two studies (a case report and a small observational study) have examined the effects of medical cannabis on pain in children and youth. No controlled trial has commented on long-term safety of medical cannabis. Findings from the recreational cannabis literature reveal significant potential short- and long-term risks of regular cannabis use, including impaired driving, depression, suicidality, psychosis, and tolerance. Despite this, many children and youth are self-medicating with cannabis, and perceive regular cannabis use to be safe. There is a need for better education and counselling of patients regarding the benefits and risks of medical cannabis use.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.079
GPT teacher head0.344
Teacher spread0.265 · 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 teacher head, not a consensus.

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

Citations12
Published2020
Admission routes1
Has abstractyes

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