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Record W1823951518 · doi:10.1002/erv.1119

More Than Just Milk: A Review of Prolactin's Impact on the Treatment of Anorexia Nervosa

2011· review· en· W1823951518 on OpenAlexaff
Melanie Strike, Sandhaya Norris, Sarah Kearney, Mark L. Norris

Bibliographic record

VenueEuropean Eating Disorders Review · 2011
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsChildren's Hospital of Eastern OntarioMcMaster UniversityMcMaster Children's HospitalRoyal Ottawa Mental Health CentreOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsAnorexia nervosaProlactinAffect (linguistics)Eating disordersAdverse effectPsychologyMenstruationAnorexiaPsychotherapistMedicineClinical psychologyHormonePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: In completing this review, we aim to educate readers about the physiological importance of the hormone prolactin (PRL) in the treatment of patients with anorexia nervosa (AN). METHOD: A comprehensive review of PRL was undertaken using existing published literature with specific focus on domains pertinent to the treatment of AN. RESULTS: Prolactin influences multiple biological processes throughout the body. Disruption in its regulation can impact women's health issues such as menstruation and bone health, which are pertinent to AN treatment. The use of antipsychotics with high D2 receptor affinity for the augmented treatment of AN increases the potential risk of PRL-mediated adverse effects. DISCUSSION: Although not intrinsic to underlying disease underpinnings, PRL has the capacity to affect and influence multiple outcome variables in treatment of patients with AN. Improved understanding, better screening and the completion of further prospective research are necessary to help facilitate and incorporate ongoing knowledge translation.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.098
GPT teacher head0.398
Teacher spread0.300 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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