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Record W4412425164 · doi:10.1016/j.jad.2025.119877

Impact of early-life deprivation and threat on physical, psychological, and cognitive multimorbidity: Evidence from multinational prospective cohorts

2025· article· en· W4412425164 on OpenAlexaff
Yueyue You, Xiaobing Wu, Ziyang Zhang, Zhiguang Zhao, Deliang Lv, Fengzhu Xie, Yali Lin, Wei‐Fen Xie, Qinggang Shang, Xiangfei Meng, Yingying Su

Bibliographic record

VenueJournal of Affective Disorders · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersShenzhen Science and Technology Innovation ProgramNational Institute on AgingScience and Technology Planning Project of Shenzhen MunicipalityNational Institutes of HealthHorizon 2020 Framework ProgrammeScience, Technology and Innovation Commission of Shenzhen MunicipalityPeking UniversityNational Natural Science Foundation of ChinaSanming Project of Medicine in ShenzhenShenzhen Municipal Science and Technology Innovation CouncilEuropean CommissionUniversity of MichiganMinistry of Education of the People's Republic of ChinaWorld Bank Group
KeywordsMultimorbidityMultinational corporationCognitionPsychologyClinical psychologyGerontologyMedicinePsychiatryComorbidityPolitical science

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 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)0.004
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.396
Teacher spread0.365 · 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

Citations4
Published2025
Admission routes1
Has abstractno

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