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The Relationship of Personality Disorders and Axis I Clinical Disorders

2012· reference-entry· en· W1904216165 on OpenAlexaff
Paul S. Links, Jamal Y. Ansari, Fatima Fazalullasha, Ravi Shah

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComorbidityPersonality disordersPsychologyPsychiatryNational Comorbidity SurveyClinical psychologyPersonalityMedicine

Abstract

fetched live from OpenAlex

The purpose of this review is (a) to study and systematically review the recent literature examining the co-occurrence and relationships between Axis I psychiatric disorders and Axis II personality disorders (PDs), specifically the five originally proposed for DSM- 5, and (b) to consider the clinical utility of the current Axis I and II approach in DSM-IV-TR. Community surveys or prospective cohort studies were reviewed as a priority. Our review indicates that the associations between clinical disorders and PDs clearly varied within each disorder and across the five PDs. Our understanding has advanced, particularly related to the clinical utility of comorbidity; however, it seems premature to conclude that comorbidity is best conceptualized by having all disorders in a single category or by deleting disorders so that comorbidity no longer occurs. Our review suggests some priorities for future research into comorbidity such as including PDs in future multivariate comorbidity models.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.098
GPT teacher head0.403
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2012
Admission routes1
Has abstractyes

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