{"id":"W4402393947","doi":"10.51731/cjht.2024.969","title":"The Paige Prostate Suite: Assistive Artificial Intelligence for Prostate Cancer Diagnosis","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Suite; Prostate cancer; Prostate; Medicine; Artificial intelligence; Cancer; Computer science; Internal medicine; Archaeology; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001540366,0.000147093,0.0003004239,0.0004346484,0.0007162651,0.000170502,0.0002240741,0.000141019,0.0000246347],"category_scores_gemma":[0.002058114,0.00009711304,0.0001193765,0.0005866111,0.0003852407,0.0001327239,0.00001147095,0.0005810954,0.00001228342],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009084889,"about_ca_system_score_gemma":0.009069446,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01058168,"about_ca_topic_score_gemma":0.02294244,"domain_scores_codex":[0.9979227,0.00005254608,0.0009805351,0.0002053829,0.0001757304,0.0006631484],"domain_scores_gemma":[0.9980555,0.0006855415,0.0002861571,0.0002079945,0.0006025054,0.0001623143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005800147,0.00001297074,0.005493484,0.0003086108,0.00004031376,0.00003444897,0.001678417,0.00001164521,0.000006322968,0.003211463,0.009982159,0.9791622],"study_design_scores_gemma":[0.00003415874,0.001968642,0.003076507,0.00251648,0.00008612527,0.0001700859,0.03929702,0.0006719848,0.01343718,0.09119823,0.8472812,0.0002624294],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1025193,0.2827781,0.002565983,0.6045709,0.00486597,0.002272736,0.0001792968,0.0002075227,0.00004016533],"genre_scores_gemma":[0.9865689,0.01165775,0.0003558528,0.0005598824,0.0001341115,0.0005294945,0.000005918411,0.00002513475,0.0001629255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9788997,"threshold_uncertainty_score":0.9965482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1645874920581885,"score_gpt":0.4392394186078883,"score_spread":0.2746519265496998,"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."}}