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Record W4413981541 · doi:10.1139/jpn.0927

Influence of androgen receptor repeat polymorphisms on personality traits in men

2009· article· en· W4413981541 on OpenAlexvenueno aff
Lars Westberg, Susanne Henningsson, Mikael Landén, Kristina Annerbrink, Jonas Melke, Staffan Nilsson, Roland Rosmond, Göran Holm, Henrik Anckarsäter, Elias Eriksson

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSexual Differentiation and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAndrogen receptorBig Five personality traitsGeneticsPersonalityPsychologyBiologyClinical psychologyDevelopmental psychologyInternal medicineMedicineSocial psychologyProstate cancer

Abstract

fetched live from OpenAlex

Background: Testosterone has been attributed importance for various aspects of behaviour. The aim of our study was to investigate the potential influence of 2 functional polymorphisms in the amino terminal of the androgen receptor on personality traits in men. Methods: We assessed and genotyped 141 men born in 1944 recruited from the general population. We used 2 different instruments: the Karolinska Scales of Personality and the Temperament and Character Inventory. For replication, we similarly assessed 63 men recruited from a forensic psychiatry study group. Results: In the population-recruited sample, the lengths of the androgen receptor repeats were associated with neuroticism, extraversion and self-transcendence. The association with extraversion was replicated in the independent sample. Limitations: Our 2 samples differed in size; sample 1 was of moderate size and sample 2 was small. In addition, the homogeneity of sample 1 probably enhanced our ability to detect significant associations between genotype and phenotype. Conclusion: Our results suggest that the repeat polymorphisms in the androgen receptor gene may influence personality traits in men.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.216

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 head0.012
GPT teacher head0.269
Teacher spread0.256 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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