{"id":"W4409619030","doi":"10.2196/72522","title":"Evaluating an AI Chatbot “Prostate Cancer Info” for Providing Quality Prostate Cancer Screening Information: Cross-Sectional Study","year":2025,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Prostate cancer; Chatbot; Medicine; Quality (philosophy); Computer science; Cancer; World Wide Web; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02848211,0.0005348422,0.0007209421,0.001512956,0.001989,0.002002843,0.0009094952,0.001435204,0.002438118],"category_scores_gemma":[0.057168,0.00105466,0.001106431,0.001075204,0.001416274,0.002240667,0.001677068,0.002149483,0.000882439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002193897,"about_ca_system_score_gemma":0.002588436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0110701,"about_ca_topic_score_gemma":0.01306525,"domain_scores_codex":[0.9861727,0.008139006,0.001114062,0.001319143,0.002333507,0.0009216788],"domain_scores_gemma":[0.9356567,0.03356354,0.009174333,0.002527582,0.01513149,0.003946396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001112407,0.00915888,0.9138212,0.0007557639,0.0003613191,0.0004743557,0.05599955,0.0002228695,0.0008130479,0.0002413625,0.001340895,0.01569834],"study_design_scores_gemma":[0.0001953795,0.01500224,0.9311604,0.0003444411,0.0002892046,0.0005069033,0.04533058,0.001334718,0.001072994,0.0001197048,0.004554306,0.00008903277],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979435,0.0001330046,0.000323436,0.00006415827,0.000014253,0.0006581325,0.0001439215,0.000008921221,0.0007105184],"genre_scores_gemma":[0.9959551,0.0002114294,0.001039139,0.0002481331,0.00001782634,0.001480679,0.0002653303,0.00002250634,0.0007598987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02848211,"threshold_uncertainty_score":0.1506296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3580154689594601,"score_gpt":0.6265171370645302,"score_spread":0.26850166810507,"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."}}