{"id":"W4387381765","doi":"10.48083/adai9602","title":"How to Prevent Kidney Stones: What Is Online Video Content Imparting to Our Patients?","year":2023,"lang":"fr","type":"article","venue":"Société Internationale d’Urologie Journal","topic":"Patient Dignity and Privacy","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kidney stones; Content (measure theory); Computer science; Online video; Multimedia; Medicine; Internal medicine; Mathematics","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":[0.005855346,0.000154043,0.0003166645,0.001109638,0.0008465637,0.003016839,0.0004822676,0.001031592,0.005699294],"category_scores_gemma":[0.08206375,0.0001178966,0.000332281,0.0008598046,0.001520488,0.00328848,0.001248556,0.001007984,0.0006997061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184976,"about_ca_system_score_gemma":0.001627843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00331591,"about_ca_topic_score_gemma":0.00366866,"domain_scores_codex":[0.9930283,0.003527366,0.0006816848,0.0003290489,0.001921075,0.0005125075],"domain_scores_gemma":[0.9607834,0.02115537,0.01258691,0.0007724231,0.003149908,0.001552118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005562288,0.0002913629,0.6052483,0.003432771,0.0001836881,0.001215991,0.02848543,0.0002109238,0.000690149,0.003607927,0.01086324,0.345214],"study_design_scores_gemma":[0.00008278065,0.001691176,0.6913023,0.01453019,0.0009043842,0.01620209,0.1088199,0.002167035,0.003813556,0.01110024,0.1491102,0.0002760879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8618172,0.03756766,0.002873089,0.05371359,0.0005434547,0.0003169426,0.002220279,0.00005958217,0.04088811],"genre_scores_gemma":[0.9825943,0.009877805,0.001839559,0.003881176,0.0003729975,0.0000777694,0.0002940509,0.00001613833,0.001046286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005855346,"threshold_uncertainty_score":0.0309664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1698402417292698,"score_gpt":0.3937090605502556,"score_spread":0.2238688188209859,"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."}}