{"id":"W4407675203","doi":"10.1097/sla.0000000000006671","title":"Recovery Patterns","year":2025,"lang":"en","type":"article","venue":"Annals of Surgery","topic":"Enhanced Recovery After Surgery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Medicine; Medoid; Cluster analysis; Concomitant; Cluster (spacecraft); Physical therapy; Surgery; Artificial intelligence; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005331556,0.0001299558,0.0005409263,0.0004645532,0.00002386935,0.000008374956,0.00005653077,0.0001017554,0.0002259547],"category_scores_gemma":[0.0004806786,0.0001212769,0.0004240826,0.0003882539,0.00004414289,0.0001378349,0.00004358348,0.0001307164,0.00003507591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001120832,"about_ca_system_score_gemma":0.0001987019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003216226,"about_ca_topic_score_gemma":0.000002066408,"domain_scores_codex":[0.9988008,0.00004458884,0.0004720999,0.0002214756,0.0001876379,0.000273416],"domain_scores_gemma":[0.9983456,0.0008523578,0.0001217408,0.0004139423,0.0001884631,0.00007796699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004679835,0.0002565874,0.6778342,0.0007027009,0.0003106601,0.0001033086,0.00002160727,0.000004510623,0.003125794,0.00009038178,0.1834455,0.1336368],"study_design_scores_gemma":[0.0001547329,0.00003604617,0.7547976,0.001723836,0.00004302564,0.0000156829,0.00003149698,0.00000682323,0.2167798,0.0006396095,0.025603,0.0001682308],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821474,0.001235416,0.0005787702,0.003354877,0.001029131,0.0001050469,0.00002143719,0.00006455783,0.01146334],"genre_scores_gemma":[0.9870512,0.002620769,0.00007230131,0.005213847,0.00009574066,0.00001444818,0.00002504834,0.00001587946,0.004890732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2136541,"threshold_uncertainty_score":0.4945529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1459657466265198,"score_gpt":0.3541100763665354,"score_spread":0.2081443297400156,"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."}}