MétaCan
Menu
Back to cohort
Record W4214821837 · doi:10.5114/pedm.2022.113814

Does anorexia nervosa with adolescent onset need long-term follow-up?

2022· editorial· en· W4214821837 on OpenAlexaff
Małgorzata Waśniewska, Alessandra Li Pomi

Bibliographic record

VenuePediatric Endocrinology Diabetes and Metabolism · 2022
Typeeditorial
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsAnorexia nervosaPerfectionism (psychology)Vulnerability (computing)EtiologyDiseasePsychologyDevelopmental psychologyEating disordersBeautyAnorexiaPsychiatryClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Anorexia nervosa (AN) is a disease mainly of the female sex (90-95% of cases). Almost exclusive, in the past, of the middle-upper classes, in more recent years it has spread to all social strata. The origin and course of eating disorders (ED) are determined, due to the multifactorial etiology, by a plurality of variables, none of which, alone, is capable of triggering the disease or influencing its course and outcome. Therefore, to understand them in full, it is necessary to take due consideration of biological, psychological and evolutionary factors. The role of some conditions present since birth or childhood, such as genetic vulnerability, family environment and traumatic experiences is not yet well understood in AN pathogenesis. In many cases, some individual characteristics such as perfectionism, low self-esteem, poor ability to regulate emotions, difficulty in conscious management of the body and body image in adolescence precede the onset of ED. Certainly, socio-cultural factors also favor the development of these disorders, in particular the association of thinness with beauty and personal success.

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)0.003
metaresearch head score (Gemma)0.022
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.008
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.000
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0020.002

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 head0.009
GPT teacher head0.263
Teacher spread0.255 · 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
GenreEditorial

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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePediatric Endocrinology Diabetes and MetabolismSame topicEating Disorders and BehaviorsFrench-language works237,207