{"id":"W4414015749","doi":"10.11159/mvml25.134","title":"AI ASSISTED COMPUTATIONAL FRAMEWORK FOR PERSONALIZED KNEE IMPLANT DESIGN","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Total Knee Arthroplasty Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Implant; Human–computer interaction; Medicine; Surgery","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":[0.0005302365,0.0007929127,0.0007480896,0.0005632787,0.0004087211,0.001160652,0.001606194,0.001272464,0.003644274],"category_scores_gemma":[0.001158447,0.0005953188,0.001107878,0.0003271548,0.0007949008,0.0005322564,0.001460569,0.001030887,0.0005849227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007734512,"about_ca_system_score_gemma":0.001288233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00616578,"about_ca_topic_score_gemma":0.006189138,"domain_scores_codex":[0.9997643,0.00005971413,0.00001170294,0.00004005998,0.00009390616,0.0000303751],"domain_scores_gemma":[0.9996392,0.0001939975,0.00003340818,0.00003262575,0.00007131109,0.00002963761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009747007,0.00001098284,0.0001384708,0.00002838851,0.00001209419,0.0000319843,0.00001589279,0.9842009,0.0008413263,0.007535734,0.0003142434,0.006860228],"study_design_scores_gemma":[0.00000230988,0.000004599848,0.00001488348,0.000002471206,0.000001826712,0.000004758784,0.000002349139,0.9970239,0.0001035093,0.002301825,0.0005361387,0.000001409763],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006716597,0.0002454131,0.9874671,0.0002103779,0.00004414558,0.00005433195,0.0001071278,0.0005273991,0.004627535],"genre_scores_gemma":[0.4406411,0.0006625719,0.5488168,0.0002829446,0.00009042643,0.0006463894,0.0004820947,0.0002694557,0.008108221],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00616578,"threshold_uncertainty_score":0.01225978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01195369016031085,"score_gpt":0.257182857470036,"score_spread":0.2452291673097252,"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."}}