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Record W4387026668 · doi:10.1016/s2215-0366(23)00265-1

International consensus on patient-centred outcomes in eating disorders

2023· review· en· W4387026668 on OpenAlexafffund
Amelia Austin, Umanga de Silva, Christiana Ilesanmi, Theerawich Likitabhorn, Isabel Miller, Maria da Luz Sousa Fialho, S. Bryn Austin, Belinda Caldwell, Chu Shan Elaine Chew, Sook Ning Chua, Suzanne Dooley‐Hash, James Downs, Carine el Khazen Hadati, Beate Herpertz‐Dahlmann, Jillian Lampert, Yael Latzer, Paulo P. P. Machado, Sarah Maguire, Madeeha Malik, Carolina Meira Moser, Elissa Myers, Iris Ruth Pastor, Janice Russell, Lauren Smolar, Howard Steiger, Elizabeth Tan, Eva Trujillo, Mei‐Chih Meg Tseng, Eric F. van Furth, Jennifer E. Wildes, Christine M. Peat, Tracy K. Richmond

Bibliographic record

VenueThe Lancet Psychiatry · 2023
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteUniversity of Calgary
FundersMaternal and Child Health BureauFundação para a Ciência e a TecnologiaCumming School of Medicine, University of CalgaryAgency for Healthcare Research and QualitySubstance Abuse and Mental Health Services AdministrationBundesministerium für Bildung und ForschungWorld Health OrganizationHealth Resources and Services AdministrationNational Eating Disorders Association
KeywordsEating disordersAnxietyPatient Health QuestionnaireClinical psychologyMental healthPsychiatryPsychologyGeneralized anxiety disorderQuality of life (healthcare)Depression (economics)MedicineDepressive symptoms

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.087
GPT teacher head0.389
Teacher spread0.303 · 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.

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

Citations44
Published2023
Admission routes2
Has abstractno

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