{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003505526,0.0004246444,0.001752771,0.000652797,0.0006905806,0.00003859583,0.0001114337,0.0000405487,0.0009469193],"category_scores_gemma":[0.000412877,0.0002806072,0.0003393807,0.001497236,0.0002887969,0.0003039341,0.0001189703,0.000347591,0.000008232223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009605705,"about_ca_system_score_gemma":0.0004604526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006161811,"about_ca_topic_score_gemma":0.0002717299,"domain_scores_codex":[0.9970342,0.0000556332,0.0006833987,0.0006729969,0.0009741445,0.000579616],"domain_scores_gemma":[0.998187,0.0003896423,0.0003276493,0.000446108,0.0003222796,0.0003273077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005498326,0.0006037352,0.9880321,0.0001013193,0.001384504,0.00002371778,0.00524204,0.0001442034,0.00001402244,0.0002006176,0.001587566,0.002116355],"study_design_scores_gemma":[0.009014882,0.01466734,0.9571286,0.0001003625,0.0003550587,0.0000330874,0.007828928,0.0003160009,0.00001031517,0.00001079251,0.01019099,0.000343638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886283,0.000191845,0.0009517689,0.005312645,0.000247058,0.003497597,0.0003018254,0.0001562934,0.0007126594],"genre_scores_gemma":[0.9900436,0.00001759057,0.0004750983,0.001871102,0.0001270991,0.001688842,0.001157375,0.00006959259,0.004549658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03090348,"threshold_uncertainty_score":0.9999663,"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."}}