{"id":"W4311824302","doi":"10.1080/10503307.2022.2156306","title":"Detecting defense mechanisms from Adult Attachment Interview (AAI) transcripts using machine learning","year":2022,"lang":"en","type":"article","venue":"Psychotherapy Research","topic":"Psychopathy, Forensic Psychiatry, Sexual Offending","field":"Psychology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa; Carleton University","funders":"","keywords":"Psychology; Interview; Undoing; Denial; Sample (material); Coding (social sciences); Artificial intelligence; Clinical psychology; Psychotherapist; Machine learning; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004767016,0.0005688563,0.0006563023,0.0009484898,0.001842112,0.0001784706,0.00137208,0.0002003445,0.01517681],"category_scores_gemma":[0.00004423085,0.0006068405,0.000368728,0.00171584,0.000192516,0.0001649813,0.0001403153,0.003280078,0.0003680853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005169454,"about_ca_system_score_gemma":0.0001012397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003038418,"about_ca_topic_score_gemma":0.0004790633,"domain_scores_codex":[0.9890684,0.00468263,0.0009348647,0.00163899,0.001873228,0.001801828],"domain_scores_gemma":[0.9972103,0.0005656315,0.0003041441,0.001301202,0.0002203912,0.0003983665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01137607,0.005191773,0.02551223,0.0002266309,0.003385714,0.0007530221,0.100197,0.000638878,0.4341465,0.03185942,0.05948297,0.3272297],"study_design_scores_gemma":[0.03700239,0.01592996,0.006658034,0.00110173,0.0003599776,0.001418036,0.08167128,0.02661334,0.008086511,0.138384,0.6763918,0.00638295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8193117,0.01743679,0.04173583,0.003257882,0.09845831,0.002586981,0.0003225873,0.0007844421,0.01610545],"genre_scores_gemma":[0.9866846,0.00037802,0.005429718,0.002045817,0.00166941,0.0007145402,0.00009208914,0.000419716,0.002566098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6169088,"threshold_uncertainty_score":0.9996383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1707771328904057,"score_gpt":0.4287139979400157,"score_spread":0.25793686504961,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}