{"id":"W4399358136","doi":"10.5489/cuaj.8830","title":"Poster Session 5: Training, Education, AI","year":2024,"lang":"en","type":"article","venue":"Canadian Urological Association Journal","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kinematics; Computer science; Match moving; Simulation; Lever; Movement assessment; Motion (physics); Computer vision; Artificial intelligence; Medicine; Physics; Engineering; Mechanical engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002240109,0.001204585,0.0007541516,0.001640026,0.00139082,0.003042837,0.001144198,0.002690181,0.5014423],"category_scores_gemma":[0.003265165,0.0002758932,0.0006451851,0.0008476865,0.0004668937,0.00172433,0.005016112,0.002208742,0.2541487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008373,"about_ca_system_score_gemma":0.002238967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007021601,"about_ca_topic_score_gemma":0.001663025,"domain_scores_codex":[0.9986734,0.0003093378,0.00009430897,0.0002459292,0.0003748267,0.000302315],"domain_scores_gemma":[0.9964072,0.0002175954,0.0001030755,0.0001386441,0.0008543162,0.002279136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003121007,0.0006499506,0.00106984,0.0008347419,0.00001394406,0.0001757518,0.0004327242,0.0001455326,0.001821477,0.001497898,0.6612509,0.3317952],"study_design_scores_gemma":[0.00005068783,0.0004770933,0.005890729,0.0006457388,0.00001153565,0.0004209635,0.0004510032,0.0001684881,0.0005088685,0.001884162,0.9894712,0.00001948588],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0169775,0.01597297,0.01239761,0.04220334,0.05557738,0.001887969,0.004762781,0.003059428,0.8471609],"genre_scores_gemma":[0.04764751,0.0119223,0.008487744,0.008807309,0.01744949,0.001481397,0.002905916,0.0006508213,0.9006476],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5014423,"threshold_uncertainty_score":0.7111321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02481594019043984,"score_gpt":0.2974406775304959,"score_spread":0.2726247373400561,"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."}}