{"id":"W4365398067","doi":"10.2139/ssrn.4403111","title":"Mako Robotic-Assisted TKA Accurately Predicts Final Balance Prior to Bony Resection","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Hip and Knee Clinic","funders":"","keywords":"Resection; Balance (ability); Computer science; Artificial intelligence; Medicine; Surgery; Physical medicine and rehabilitation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002481321,0.0007185322,0.0005287888,0.0007436526,0.0002528498,0.0009643841,0.0003404115,0.0006682039,0.004223536],"category_scores_gemma":[0.001990089,0.0002128045,0.0004357344,0.0003261185,0.0002414871,0.0006303489,0.0005045319,0.0002477277,0.002155978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001697385,"about_ca_system_score_gemma":0.0002049733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001743045,"about_ca_topic_score_gemma":0.004922193,"domain_scores_codex":[0.9998333,0.00001895291,0.00002197444,0.00004742638,0.00003013057,0.00004814352],"domain_scores_gemma":[0.999451,0.0001341796,0.0001928446,0.00004205363,0.0001048781,0.00007509565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005155409,0.000157035,0.8800597,0.0002688735,0.0002949631,0.0003496856,0.0001167485,0.00206279,0.01906351,0.0001246171,0.002598876,0.08974785],"study_design_scores_gemma":[0.00003390872,0.0005816823,0.9871207,0.00007038115,0.0001905436,0.001351451,0.0001775833,0.006116975,0.00255189,0.00030382,0.001453289,0.00004772957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887344,0.001464728,0.002360179,0.0001409991,0.0002004408,0.0000228444,0.001278626,0.0001979415,0.005599857],"genre_scores_gemma":[0.9977684,0.0001582587,0.0004524117,0.00003562239,0.00003651207,0.00001147816,0.0006173912,0.00001632725,0.0009036024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004223536,"threshold_uncertainty_score":0.0141291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05709058015681477,"score_gpt":0.3380692942977735,"score_spread":0.2809787141409588,"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."}}