{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003265875,0.001324751,0.001021136,0.002459296,0.0007580651,0.004073848,0.00205732,0.001724269,0.01497489],"category_scores_gemma":[0.01212186,0.0006630913,0.001028936,0.001948438,0.0008915904,0.002861639,0.003365915,0.002863671,0.01024355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154179,"about_ca_system_score_gemma":0.002929023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009514852,"about_ca_topic_score_gemma":0.01362822,"domain_scores_codex":[0.9974301,0.0007441409,0.0001231326,0.0002928201,0.001222154,0.0001874924],"domain_scores_gemma":[0.9959962,0.001499606,0.0001770903,0.0004571556,0.001329562,0.0005402727],"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":[0.0003389248,0.0001578376,0.005711047,0.0007662863,0.0001900103,0.000385989,0.0002775911,0.003203614,0.002885771,0.005617218,0.2733459,0.7071197],"study_design_scores_gemma":[0.0002463113,0.0007178911,0.009840729,0.001129305,0.0002317867,0.002773123,0.0004815675,0.06114677,0.01048453,0.02981627,0.8828075,0.0003241548],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0295538,0.07130466,0.5266452,0.05458068,0.006142795,0.002166267,0.01683174,0.1504451,0.1423298],"genre_scores_gemma":[0.1888083,0.0525032,0.6569512,0.01958499,0.004181781,0.001196291,0.0234765,0.006802026,0.0464957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9904851,"threshold_uncertainty_score":0.05009598,"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."}}