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Record W2035859048 · doi:10.1002/jts.20452

Identifying PTSD personality subtypes in a workplace trauma sample

2009· article· en· W2035859048 on OpenAlexaff
Martin Sellbom, R. Michael Bagby

Bibliographic record

VenueJournal of Traumatic Stress · 2009
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologyAngerClinical psychologyAnhedoniaPsychopathologyMinnesota Multiphasic Personality InventoryPersonalityPsychiatryAggressionHostilityBorderline personality disorderDistressAntisocial personality disorderPoison controlMoodPersonality disordersInjury preventionMedicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

The authors sought to identify personality clusters derived from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) Personality Psychopathology Five Scales in a sample of workplace claimants with posttraumatic stress disorder (PTSD). Three clusters--low pathology, internalizing, and externalizing were recovered similar to those obtained by M. W. Miller and colleagues (2003, 2004, 2007) in samples of combat veterans and sexual assault victims. Internalizers and externalizers scored comparably on measures of PTSD symptom severity, general distress, and negative affect. Internalizers were uniquely characterized by anhedonia and depressed mood; externalizers by antisocial behavior, substance abuse, and anger/aggression.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.125
GPT teacher head0.418
Teacher spread0.293 · 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

Citations38
Published2009
Admission routes1
Has abstractyes

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