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Record W2077139373 · doi:10.1097/wnr.0b013e3283637845

Between-site reliability of startle prepulse inhibition across two early psychosis consortia

2013· article· en· W2077139373 on OpenAlexaff
Kristin S. Cadenhead, Jean Addington, Tyrone D. Cannon, Barbara A. Cornblatt, Camilo de la Fuente‐Sandoval, Daniel H. Mathalon, Diana O. Perkins, Larry J. Seidman, Ming T. Tsuang, Elaine F. Walker, Scott W. Woods, Peter Bachman, Ayşenil Belger, Ricardo E. Carrión, Franc C. L. Donkers, Erica Duncan, Jason Johannesen, Pablo León-Ortíz, Gregory A. Light, Alejandra Mondragón, Margaret Niznikiewicz, Jason Nunag, Brian J. Roach, Rodolfo Solís‐Vivanco

Bibliographic record

VenueNeuroreport · 2013
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Calgary
FundersNational Institute of Mental HealthUniversity of California, San Diego
KeywordsPrepulse inhibitionStartle responseIntraclass correlationPsychologyPsychosisSchizophrenia (object-oriented programming)Reliability (semiconductor)Clinical psychologyPsychometricsPsychiatryNeuroscience

Abstract

fetched live from OpenAlex

Prepulse inhibition (PPI) and reactivity of the acoustic startle response are widely used biobehavioral markers in psychopathology research. Previous studies have demonstrated that PPI and startle reactivity exhibit substantial within-site stability; however, between-site stability has not been established. In two separate consortia investigating biomarkers of early psychosis, traveling participants studies were carried out as a part of quality assurance procedures to assess the fidelity of data across sites. In the North American Prodromal Longitudinal Studies (NAPLS) consortium, eight normal participants traveled to each of the eight NAPLS sites and were tested twice at each site on the startle PPI paradigm. In preparation for a binational study, 10 healthy participants were assessed twice in both San Diego and Mexico City. Intraclass correlations between and within sites were significant for PPI and startle response parameters, confirming the reliability of startle measures across sites in both consortia. There were between-site differences in startle magnitude in the NAPLS study that did not appear to be related to methods or equipment. In planning multisite studies, it is essential to institute quality assurance procedures early and establish between-site reliability to assure comparable data across sites.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.044
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.341
Teacher spread0.313 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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