{"id":"W3215710945","doi":"10.1186/s13040-021-00281-8","title":"Development of glaucoma predictive model and risk factors assessment based on supervised models","year":2021,"lang":"en","type":"article","venue":"BioData Mining","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Glaucoma; Machine learning; Artificial intelligence; Data science; Risk analysis (engineering); Medicine; Ophthalmology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00142654,0.0007183402,0.0008330918,0.001304622,0.0003537263,0.000787708,0.001142554,0.0006513964,0.00117783],"category_scores_gemma":[0.003290062,0.0003071167,0.001129514,0.000569972,0.0002151338,0.0008191183,0.0005796239,0.0009260851,0.000383031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005192049,"about_ca_system_score_gemma":0.001183498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007316375,"about_ca_topic_score_gemma":0.005520941,"domain_scores_codex":[0.9994029,0.0001621062,0.00004853719,0.0001647108,0.0001579642,0.00006388593],"domain_scores_gemma":[0.9988939,0.0004646003,0.0001188328,0.00006447873,0.0004151081,0.0000430876],"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":[0.0002117416,0.0004035885,0.05035126,0.0001832972,0.0003518265,0.0003522364,0.0001754497,0.6625355,0.002981833,0.005085335,0.005277843,0.27209],"study_design_scores_gemma":[0.000004885473,0.00003222561,0.001796001,0.0000150627,0.00002578553,0.00003697596,0.00001333179,0.9961011,0.0003055394,0.001313227,0.0003492044,0.000006667652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1171857,0.0009363557,0.8764417,0.0006300721,0.0001171386,0.0002199846,0.0006652683,0.001072099,0.00273173],"genre_scores_gemma":[0.8676763,0.0007224717,0.1268944,0.00017827,0.0001744233,0.0004017408,0.001258466,0.00004378655,0.002650176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007316375,"threshold_uncertainty_score":0.01454759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05509305354175464,"score_gpt":0.3059507429795755,"score_spread":0.2508576894378208,"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."}}