{"id":"W4391057179","doi":"10.1093/schbul/sbae001","title":"Eye Movement Characteristics for Predicting a Transition to Psychosis: Longitudinal Changes and Implications","year":2024,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Schizophrenia research and treatment","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Longitudinal study; Random forest; Psychosis; Eye movement; Fixation (population genetics); Psychology; Eye tracking; Regression; Predictive power; Generalized estimating equation; Saccade; Observational study; Regression analysis; Audiology; Statistics; Artificial intelligence; Computer science; Medicine; Mathematics; Psychiatry; Neuroscience; Physics","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":[0.0002348839,0.0002105908,0.0002580595,0.0002366671,0.0001797646,0.0001298563,0.0000673355,0.00007512729,0.0001720009],"category_scores_gemma":[0.00008119897,0.0001802612,0.00009370255,0.0002200112,0.00004167491,0.00002756839,0.00003443322,0.0001705444,0.000120457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009536143,"about_ca_system_score_gemma":0.00008230296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002987319,"about_ca_topic_score_gemma":0.00006934474,"domain_scores_codex":[0.9985982,0.00002259933,0.000236066,0.0005359018,0.0002267925,0.0003804134],"domain_scores_gemma":[0.999131,0.0001015077,0.00002879139,0.0002645463,0.0001077806,0.0003663483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0353032,0.001023135,0.01613602,0.002329366,0.001522063,0.0001792521,0.001814836,0.000004366897,0.02089064,0.01929908,0.04484368,0.8566543],"study_design_scores_gemma":[0.01287272,0.006021018,0.8380291,0.002964813,0.001306005,0.0002239142,0.000342115,0.002273604,0.005130459,0.005211306,0.1246619,0.0009630254],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8021517,0.001744999,0.004237025,0.1885859,0.0002424752,0.002129315,0.0005065254,0.0002818634,0.0001201623],"genre_scores_gemma":[0.9772667,0.0002872979,0.01831917,0.0009771336,0.0007485054,0.001776217,0.0002059015,0.00005146999,0.0003676153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8556913,"threshold_uncertainty_score":0.7350839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0237225424940801,"score_gpt":0.3127862472755128,"score_spread":0.2890637047814327,"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."}}