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Record W2095905528 · doi:10.1177/0963721410378360

Prenatal Factors in Schizophrenia

2010· article· en· W2095905528 on OpenAlexaff
Suzanne King, Annie St‐Hilaire, David Heidkamp

Bibliographic record

VenueCurrent Directions in Psychological Science · 2010
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsConcordia UniversityMcGill UniversityDouglas Mental Health University InstituteDouglas College
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyDiseaseRisk factorPregnancyDevelopmental psychologyPsychiatryMedicineGeneticsBiology

Abstract

fetched live from OpenAlex

The purpose of this review is to summarize the current state of knowledge on how nongenetic factors occurring before, during, or soon after birth are related to schizophrenia. Schizophrenia is a complex psychiatric illness with a varied clinical presentation that has both environmental and genetic origins and that may result from insults to the nervous system that occur throughout development. In line with this, several endogenous (internal) and exogenous (external) nongenetic factors of pregnancy and birth have been related to an increased risk for schizophrenia in later life. These factors include maternal diabetes, low birth weight, older paternal age, winter birth, and prenatal maternal stress, among others. Although each of these nongenetic factors alone slightly increases the risk for schizophrenia, risk increases when these factors combine with each other and with other risk factors. The mechanisms that link each specific risk factor with the occurrence of schizophrenia remain largely unknown. In order to build better models of the illness, researchers will have to address the question of how environmental and genetic risk factors work together in increasing risk and explore to what extent certain underlying risk factors may explain different aspects of the disease.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.099
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.422
Teacher spread0.358 · 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.

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

Citations23
Published2010
Admission routes1
Has abstractyes

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