{"id":"W3128287206","doi":"10.7939/r3-h1kz-gs07","title":"MODELLING EARLY DETECTION OF PROSTATE CANCER","year":2019,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prostate cancer; Prostate; Cancer; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009552572,0.0007678062,0.00068382,0.0006690348,0.0002948247,0.001235869,0.0009646643,0.001229966,0.002331027],"category_scores_gemma":[0.004296984,0.0004285594,0.001005215,0.00069711,0.0003972758,0.0007200282,0.0006255023,0.001192239,0.0004924224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007867331,"about_ca_system_score_gemma":0.001168503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02085795,"about_ca_topic_score_gemma":0.01374798,"domain_scores_codex":[0.9996215,0.0001026839,0.00002091634,0.0001253464,0.00005719806,0.00007220796],"domain_scores_gemma":[0.9982828,0.001293857,0.0001635806,0.00004098827,0.0001654949,0.00005318129],"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":[0.0001309352,0.00007291005,0.01498558,0.0001372487,0.00007452669,0.0001682845,0.00007421773,0.9591967,0.0009548635,0.004116915,0.001080428,0.01900733],"study_design_scores_gemma":[0.000004294524,0.00002106142,0.001158022,0.00000581675,0.00001025119,0.00002081217,0.000007262088,0.9968795,0.0001844151,0.001360944,0.000341375,0.000006146127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4915524,0.002801728,0.4867909,0.002669491,0.0002420992,0.0002025505,0.005708565,0.00133876,0.008693469],"genre_scores_gemma":[0.9682505,0.0006908408,0.02301607,0.0001260783,0.00005343383,0.0001395217,0.001436474,0.00003810297,0.006249035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02085795,"threshold_uncertainty_score":0.04147309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006921831213527686,"score_gpt":0.164327641612156,"score_spread":0.1574058103986283,"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."}}