{"id":"W4400584193","doi":"10.3390/jpm14070744","title":"Natural Language Processing and Schizophrenia: A Scoping Review of Uses and Challenges","year":2024,"lang":"en","type":"review","venue":"Journal of Personalized Medicine","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"PsycINFO; Schizophrenia (object-oriented programming); Verbal fluency test; Population; Fluency; MEDLINE; Cognition; Natural language processing; Computer science; Psychology; Cognitive psychology; Medicine; Artificial intelligence; Psychiatry; Neuropsychology","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":[],"consensus_categories":[],"category_scores_codex":[0.001955664,0.0003270061,0.002586252,0.0004373695,0.00005087719,0.00003577616,0.0004591329,0.0001176192,0.00001421542],"category_scores_gemma":[0.00112526,0.0001872242,0.0001989124,0.0003769069,0.0001811614,0.0002013985,0.0001921436,0.001098203,7.369499e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004910338,"about_ca_system_score_gemma":0.0007191622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009565213,"about_ca_topic_score_gemma":0.000003754137,"domain_scores_codex":[0.9973097,0.0003667033,0.001165607,0.0003246837,0.0006397871,0.0001934567],"domain_scores_gemma":[0.9975109,0.0004234089,0.001433917,0.0002185505,0.0002414026,0.0001718688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000002625436,0.000002951128,3.196862e-7,0.4515467,0.00003968143,0.00008635678,0.0009479787,4.242373e-9,2.352396e-7,0.0001431059,0.00007121651,0.5471588],"study_design_scores_gemma":[0.0003228999,0.0001888091,0.000002136853,0.8955613,0.0007473529,0.003434513,0.0001084143,0.00007741053,6.105402e-8,0.00002286979,0.09940007,0.0001341537],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000003215056,0.9933583,0.0001129584,0.005684194,0.0003988182,0.0003667558,0.000001495604,0.00002270877,0.00005159883],"genre_scores_gemma":[0.00001298315,0.9943985,0.004657862,0.0002407344,0.0006104573,0.000005861647,0.000001546704,0.00002547217,0.00004662998],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5470247,"threshold_uncertainty_score":0.763478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09115658290020892,"score_gpt":0.4341636644784218,"score_spread":0.3430070815782128,"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."}}