{"id":"W2900083938","doi":"10.3389/fninf.2018.00077","title":"The CAMH Neuroinformatics Platform: A Hospital-Focused Brain-CODE Implementation","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Indoc Research; University of Toronto; Public Health Ontario; Baycrest Hospital; Ontario Brain Institute; Centre for Addiction and Mental Health","funders":"Canada Foundation for Innovation; Government of Ontario","keywords":"Neuroinformatics; Standardization; Computer science; Context (archaeology); Data science; Analytics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002654251,0.001073789,0.0007136389,0.001356503,0.000561368,0.001835242,0.004681087,0.0007455212,0.02247326],"category_scores_gemma":[0.009867869,0.0007407385,0.0008550313,0.001624727,0.001037416,0.001932345,0.003794355,0.001678129,0.01042587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002702755,"about_ca_system_score_gemma":0.005069422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02629648,"about_ca_topic_score_gemma":0.02640741,"domain_scores_codex":[0.9987022,0.0001997001,0.00009320349,0.0003992401,0.000485653,0.0001199769],"domain_scores_gemma":[0.997135,0.0007359788,0.0001183891,0.0008561467,0.000823446,0.0003310405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001745676,0.0003311564,0.008212048,0.00076517,0.0003596093,0.0009085098,0.001658798,0.0254451,0.01704142,0.04172034,0.6729238,0.2288884],"study_design_scores_gemma":[0.0009862597,0.0002871017,0.009632981,0.0002279307,0.0001473531,0.0006345184,0.0004991057,0.4442741,0.04778837,0.05671845,0.4384887,0.0003151903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01390293,0.00030382,0.4862669,0.001725708,0.0003164055,0.001254757,0.0278226,0.4513266,0.01708023],"genre_scores_gemma":[0.2431597,0.0006848273,0.5961255,0.001830132,0.0002058044,0.002746402,0.08732408,0.05192369,0.01599994],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02629648,"threshold_uncertainty_score":0.07518059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0237977584798663,"score_gpt":0.2733470155481162,"score_spread":0.2495492570682499,"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."}}