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Record W2118981668 · doi:10.1093/schbul/sbl075

North American Prodrome Longitudinal Study: A Collaborative Multisite Approach to Prodromal Schizophrenia Research

2007· article· en· W2118981668 on OpenAlexaff
J. Addington, Kristin S. Cadenhead, T. D. Cannon, B. Cornblatt, Thomas H. McGlashan, Diana O. Perkins, L. J. Seidman, Ming T. Tsuang, E. F. Walker, S. W. Woods, R. Heinssen

Bibliographic record

VenueSchizophrenia Bulletin · 2007
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute of Mental Health
KeywordsProdromePsychosisPsychologyPsychiatryClinical psychologySchizophrenia (object-oriented programming)Longitudinal studyProdromal StageMedicineCognitionCognitive impairment

Abstract

fetched live from OpenAlex

This article presents the rationale, design, and preliminary findings of the North American Prodrome Longitudinal Study (NAPLS), a collaborative, multisite investigation into the earliest phase of psychotic illness. We describe how 8 independently conceived research projects were integrated methodologically, how diagnostic reliability was achieved across sites on the Structured Interview for Prodromal Syndromes, and how baseline and follow-up data were aggregated for 888 at risk and comparison subjects. Data are presented describing the demographic, academic/work, and diagnostic characteristics of 3 relevant subgroups: persons at heightened clinical risk for psychosis, help-seeking comparison subjects, and nonpsychiatric controls. The NAPLS data set will be used to explore a series of questions related to prodromal psychosis, including the descriptive phenomenology of currently accepted diagnostic criteria, conversion rates over a 30-month period, predictors of psychosis onset and functional disability, and the impact of early treatment on the course of prodromal symptoms.

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)0.017
metaresearch head score (Gemma)0.011
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 score0.035
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.360
Teacher spread0.310 · 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

Citations300
Published2007
Admission routes1
Has abstractyes

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