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Record W1992504004 · doi:10.1037/0021-843x.116.3.565

P300 amplitude, externalizing psychopathology, and earlier- versus later-onset substance-use disorder.

2007· article· en· W1992504004 on OpenAlexaff
Scott R. Carlson, Megan E. McLarnon, William G. Iacono

Bibliographic record

VenueJournal of Abnormal Psychology · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of British Columbia
FundersNational Institute on Drug AbuseNational Institute on Alcohol Abuse and Alcoholism
KeywordsPsychologyPsychopathologyAge of onsetConduct disorderSubstance abuseYoung adultPsychiatryAudiologyDevelopmental psychologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

P300 amplitude predicts substance use or disorder by age 21. Earlier- versus later-onset substance disorders may reflect different levels of an externalizing psychopathology dimension. P300 in adolescence may not be as strongly related to later-onset substance problems as it is to earlier-onset ones. In the present study, visual P300 amplitude was measured at age 17 in a community-representative sample of young men. Substance and externalizing disorders were assessed at approximately ages 17, 20, and 24. Earlier-onset (by age 20) substance disorder was associated with higher rates of externalizing disorders than were later-onset problems. P300 amplitude was reduced in subjects with earlier-onset substance disorders, relative to later-onset and disorder-free subjects. Amplitude was also reduced in subjects with an externalizing disorder but no substance disorder. Earlier-onset subjects had reduced P300, even in the absence of an externalizing disorder. The results could not be attributed to a concurrent disorder or to recent substance use at the time of the P300 recording. The findings are consistent with P300 indexing an externalizing spectrum. Earlier-onset substance disorders are more strongly related to P300 and externalizing than are later-onset problems.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.062
GPT teacher head0.360
Teacher spread0.298 · 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.

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

Citations46
Published2007
Admission routes1
Has abstractyes

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