{"id":"W4416974652","doi":"10.1007/s11126-025-10232-9","title":"Psychiatric Inpatient Length of Stay and Needs: A Cluster Analysis using Machine Learning Algorithms","year":2025,"lang":"en","type":"article","venue":"Psychiatric Quarterly","topic":"Schizophrenia research and treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centres Intégré Universitaires de Santé et de Services Sociaux; Institut Universitaire en Santé Mentale de Québec","funders":"Canadian Institutes of Health Research","keywords":"Anxiety; Distress; Mood; Mood disorders; Mental health; Personality disorders; Psychopathology; Public health; Cluster (spacecraft)","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000299249,0.0002616024,0.0006215506,0.002593653,0.0001651138,0.00003789938,0.0001062054,0.0001054385,0.0000674292],"category_scores_gemma":[0.00002614931,0.0002105989,0.0003052933,0.004070983,0.00006934057,0.00008477311,0.00003101217,0.000344037,0.000007329412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009049904,"about_ca_system_score_gemma":0.0002113159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000698016,"about_ca_topic_score_gemma":0.0001706827,"domain_scores_codex":[0.998034,0.0001531838,0.0005748095,0.0004026036,0.0004403215,0.0003950716],"domain_scores_gemma":[0.9989332,0.0001133771,0.0001924557,0.000399252,0.0001415056,0.0002201998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003655089,0.001139565,0.8818868,0.0003208398,0.003982815,0.00001416911,0.001480972,0.00007764633,0.00005553783,0.0006752679,0.0002098654,0.1065014],"study_design_scores_gemma":[0.03630752,0.01438972,0.6444108,0.0001759599,0.01897426,0.0001014687,0.004346638,0.2748421,0.0001435965,0.003802363,0.001523682,0.0009818939],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850168,0.006006125,0.006231474,0.001218239,0.0002410484,0.0005853715,0.0000238092,0.00005639638,0.0006207537],"genre_scores_gemma":[0.9718094,0.0001898676,0.02724276,0.0001425692,0.0001014478,0.00002362779,0.00004519978,0.00002087064,0.0004242143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2747644,"threshold_uncertainty_score":0.8587975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121702088857839,"score_gpt":0.2931734743890101,"score_spread":0.2819564535004317,"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."}}