{"id":"W4410343201","doi":"10.2196/73265","title":"Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mental Health Research Topics","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Drug Abuse; National Institute on Alcohol Abuse and Alcoholism","keywords":"Preprint; Nomothetic and idiographic; Algorithm; Computer science; Development (topology); Space (punctuation); State space; State (computer science); Artificial intelligence; Data mining; Mathematics; Psychology; Statistics; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006705715,0.001210087,0.001164051,0.001049376,0.000464348,0.0009327075,0.001193619,0.001494066,0.002255161],"category_scores_gemma":[0.01868134,0.0004067111,0.00097258,0.000735988,0.0003671754,0.0008345593,0.001204686,0.002365926,0.0005304248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00098318,"about_ca_system_score_gemma":0.002018535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01654014,"about_ca_topic_score_gemma":0.009214032,"domain_scores_codex":[0.9988538,0.0005794392,0.00009817898,0.0002305914,0.0001386723,0.00009915484],"domain_scores_gemma":[0.9832286,0.01377286,0.0004279848,0.0006354642,0.001766696,0.0001684932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003562889,0.0004624769,0.01931222,0.000161729,0.0002483725,0.00007650984,0.00008492306,0.8502251,0.000697947,0.001790391,0.00146362,0.1251206],"study_design_scores_gemma":[0.00001354726,0.00003679645,0.0004222637,0.00000672121,0.000009920344,0.000007164673,0.000008951017,0.9990094,0.000128126,0.0002628196,0.00009158178,0.000002684803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3011293,0.00217728,0.6892662,0.0008140208,0.000121984,0.000571568,0.0006303812,0.002806192,0.00248305],"genre_scores_gemma":[0.7667153,0.0005026814,0.2296526,0.0001809855,0.00003697828,0.000612243,0.001269459,0.00008711335,0.0009426337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01654014,"threshold_uncertainty_score":0.03546363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1129738976729391,"score_gpt":0.4861933182955096,"score_spread":0.3732194206225705,"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."}}