{"id":"W4307432693","doi":"10.2196/38690","title":"Outcomes With a Mobile Digital Health Platform for Patients Undergoing Spine Surgery: Retrospective Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Perioperative Medicine","topic":"Total Knee Arthroplasty Outcomes","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health; Georgia Clinical and Translational Science Alliance","keywords":"Medicine; Perioperative; Logistic regression; Demographics; Odds ratio; Retrospective cohort study; Health care; Medical record; Surgery; General surgery; Physical therapy; 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":[0.001604591,0.0002728527,0.0005832593,0.001843836,0.0007581309,0.000977376,0.0006460016,0.0005775636,0.001985565],"category_scores_gemma":[0.005268614,0.0004594885,0.001366249,0.003208328,0.0004756783,0.001155424,0.00136689,0.001023998,0.000320783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009218064,"about_ca_system_score_gemma":0.0009209996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006787418,"about_ca_topic_score_gemma":0.007740957,"domain_scores_codex":[0.9976278,0.0003585452,0.0006134871,0.0004430238,0.0006382695,0.0003188149],"domain_scores_gemma":[0.9941298,0.0009808742,0.003453685,0.0003305158,0.0006221368,0.0004829749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007908009,0.00002892634,0.9987801,0.00005790967,0.0000642019,0.00005632063,0.00008639583,0.00001797374,0.00002540076,0.00001059635,0.0001265274,0.0006664666],"study_design_scores_gemma":[0.00001361698,0.0002251606,0.9975229,0.00007569757,0.0001180388,0.0004309164,0.001013259,0.0001892956,0.00004361022,0.00002084299,0.000335785,0.00001082881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972211,0.0006884283,0.0001056936,0.00005299262,0.00000836679,0.00008105687,0.001312216,0.000003868434,0.0005263567],"genre_scores_gemma":[0.9983884,0.0003803305,0.0001172984,0.00006636918,0.00001343276,0.00008671343,0.0008671087,0.000003552623,0.00007677609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006787418,"threshold_uncertainty_score":0.0134958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01615388939136482,"score_gpt":0.300446370605671,"score_spread":0.2842924812143062,"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."}}