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Record W1800548134 · doi:10.1002/eat.22229

Cannabis withdrawal syndrome: An important diagnostic consideration in adolescents presenting with disordered eating

2013· article· en· W1800548134 on OpenAlexaff
Tyler R. Chesney, Laura Matsos, Jennifer Couturier, Natasha Johnson

Bibliographic record

VenueInternational Journal of Eating Disorders · 2013
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsCannabisEating disordersPsychiatryPsychologyWeight lossPopulationDisordered eatingClinical psychologyMedicineObesityInternal medicine

Abstract

fetched live from OpenAlex

Although previously thought to have no withdrawal symptoms, there is now convergent evidence for a cannabis withdrawal syndrome (CWS), criteria for its diagnosis, and evidence of its impact in the adolescent population. Cannabis withdrawal syndrome represents an important and under-recognized consideration in adolescents with disordered eating. We describe three clinical cases of adolescents presenting to an eating disorders program with primary complaints of gastrointestinal symptoms, food avoidance, and associated weight loss. They did not meet the criteria for an eating disorder, but did fulfill the DSM-5 criteria for CWS. This report emphasizes the importance of considering the impact of heavy cannabis use in adolescents presenting with gastrointestinal complaints, and eating disorder symptoms, including weight loss.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.269
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations6
Published2013
Admission routes1
Has abstractyes

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