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Record W2046787029 · doi:10.1196/annals.1429.013

<i>Eating Disorders and Menstrual Dysfunction in Adolescents</i>

2008· review· en· W2046787029 on OpenAlexaff
Ellie Vyver, Cathleen Steinegger, Debra K. Katzman

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2008
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsEtiologyEating disordersDisordered eatingMedicinePsychologyStressorCognitionAnorexia nervosaClinical psychologyMenstrual cyclePsychiatryInternal medicineHormone

Abstract

fetched live from OpenAlex

Menstrual dysfunction is a common feature of all eating disorders and results in significant medical complications. The etiology of menstrual dysfunction is multifaceted and the result of a complex interplay of many factors including weight loss, decreased body fat, hypoleptinemia, abnormal eating attitudes and behaviors, exercise, and psychological stressors. This chapter will review the prevalence of menstrual dysfunction in adolescents with eating disorders, its multifactorial etiology, the evidence-based pathophysiology, and the resulting complications to linear growth, pubertal development, bone mineral accretion, and cognitive function. Future research directions are identified that suggest opportunities to gain new insights into our understanding of the mechanisms and treatment of menstrual dysfunction in adolescents 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.123
GPT teacher head0.398
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2008
Admission routes1
Has abstractyes

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