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Record W2166195068 · doi:10.1080/10640266.2015.1027119

Male Youth With Eating Disorders: Clinical and Medical Characteristics of a Sample of Inpatients

2015· article· en· W2166195068 on OpenAlexaff
Jennifer S. Coelho, Aarti Kumar, Megan Kilvert, Lucinda Kunkel, Pei‐Yoong Lam

Bibliographic record

VenueEating Disorders · 2015
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsBC Mental Health & Substance Use ServicesUniversity of British Columbia
Fundersnot available
KeywordsEating disordersAnorexia nervosaContext (archaeology)PsychiatryMedicineClinical psychologyPsychology

Abstract

fetched live from OpenAlex

A retrospective chart review was conducted to elucidate the clinical and medical characteristics of male youth admitted to a tertiary inpatient treatment center for eating disorders. A total of 23 male youth were identified who had received treatment between January 2003 and February 2014, and for whom charts were available. The majority of the sample (n = 19; 82.6%) received a diagnosis of anorexia nervosa, and the data suggest that these male youth were significantly medically compromised. The patterns in this data will be discussed in the context of previous published research on male youth with eating disorders.

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)0.001
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.342
Teacher spread0.299 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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