{"id":"W3208723157","doi":"10.1017/s1041610221001307","title":"100 - Artificial Intelligence in Geriatric Mental Health: Recent Advances in Clinical Research","year":2021,"lang":"en","type":"article","venue":"International Psychogeriatrics","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mental health; Psychosocial; Workforce; Psychology; Gerontology; Geriatric psychiatry; Medicine; Artificial intelligence; Psychiatry; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005529616,0.000181042,0.0002680669,0.0003698715,0.0001286484,0.000068282,0.0005225487,0.0001369385,0.0040189],"category_scores_gemma":[0.0009960987,0.0002067549,0.00007876604,0.001949398,0.0002093776,0.0004787222,0.00038025,0.000895141,0.001176738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001544506,"about_ca_system_score_gemma":0.0001750308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002371073,"about_ca_topic_score_gemma":0.002093859,"domain_scores_codex":[0.9947185,0.0009352172,0.001348915,0.00112813,0.001181698,0.0006875457],"domain_scores_gemma":[0.9986787,0.0004678857,0.0002172568,0.0003657268,0.00004709975,0.0002232994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001480663,0.001171782,0.1255025,0.0000115053,0.000006806626,0.00008841378,0.0005434776,0.0008424087,0.0002007592,0.0009506543,0.00198551,0.8685482],"study_design_scores_gemma":[0.0008762751,0.0002397159,0.3539781,0.00009806617,0.000002818048,0.00003503498,0.001380047,0.003503614,0.0003252676,0.02546567,0.6135681,0.0005272055],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8373476,0.007285067,0.007236802,0.06738935,0.01025872,0.002070598,0.0001419517,0.00008779551,0.06818213],"genre_scores_gemma":[0.8863204,0.1023126,0.006700113,0.003027185,0.0008483304,0.0001156795,0.0001383866,0.00005879091,0.0004785175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.868021,"threshold_uncertainty_score":0.9996009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1152879208088895,"score_gpt":0.475333325742882,"score_spread":0.3600454049339925,"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."}}