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Record W7033286275

Protecting women from image and eating-related difficulties: The promising role of body compassion and the bright side of non-striving

2018· article· pt· W7033286275 on OpenAlexfundno aff

Bibliographic record

VenueEstudo Geral (Universidade de Coimbra) · 2018
Typearticle
Languagept
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
FundersUniversity at AlbanyUniversity of California, San FranciscoUniversity of North Carolina at Chapel HillUniformed Services University of the Health SciencesSchool of Medicine, Stanford UniversityNational Institutes of HealthUniversity of South CarolinaUniversity of OregonUniversity of Toronto MississaugaNational Institute of Diabetes and Digestive and Kidney DiseasesKeele UniversityUniversity of California, San DiegoYale UniversityUniversity of TorontoUniversity of MissouriYork UniversityLeids Universitair Medisch CentrumUniversity of OtagoState University of New YorkVirginia Commonwealth UniversityArizona State UniversityBrown UniversityChildren's Mercy HospitalOklahoma State UniversityMassachusetts General HospitalMedical University of South CarolinaChildren's Hospital of PhiladelphiaWestern Sydney UniversityUniversity of PittsburghBill and Melinda Gates Foundation
KeywordsCompassionImpermanenceEmpathyObject (grammar)Narrative
DOInot available

Abstract

fetched live from OpenAlex

Dissertação de Mestrado Integrado em Psicologia apresentada à Faculdade de Psicologia e de Ciências da Educação

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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