{"id":"W4389080821","doi":"10.1016/j.jclinepi.2023.111226","title":"Applying sequence analysis to uncover ‘real-world’ clinical pathways from routinely collected data: a systematic review","year":2023,"lang":"en","type":"review","venue":"Journal of Clinical Epidemiology","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Keele University; Faculty of Medicine and Health, University of Sydney; Department of Health and Social Care; National Institute for Health and Care Research","keywords":"PsycINFO; CINAHL; MEDLINE; Systematic review; Identification (biology); Data science; Medicine; Hierarchical clustering; Data mining; Information retrieval; Cluster analysis; Computer science; Political science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.157932,0.00260039,0.01076916,0.03021812,0.001980628,0.008595573,0.004665931,0.003892191,0.003692204],"category_scores_gemma":[0.4822395,0.002445728,0.01183816,0.02422338,0.003857523,0.01246749,0.004526665,0.00279007,0.0006179037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009132918,"about_ca_system_score_gemma":0.04992986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005723926,"about_ca_topic_score_gemma":0.01638778,"domain_scores_codex":[0.7379494,0.1580716,0.07104226,0.008724947,0.02277045,0.001441248],"domain_scores_gemma":[0.4572701,0.4482997,0.05869798,0.01204392,0.02260398,0.001084323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001779392,0.00003538236,0.002015927,0.9322422,0.01134507,0.0001160196,0.001120882,0.0004596575,0.0001742957,0.001855416,0.001161714,0.04929552],"study_design_scores_gemma":[0.0003222294,0.0003355964,0.0024507,0.9526966,0.02712428,0.0002777537,0.001393566,0.0005507548,0.0003339019,0.002947141,0.01147895,0.00008851157],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005507873,0.9629355,0.01342341,0.002183796,0.0008394759,0.01241848,0.001662682,0.00007725229,0.000951524],"genre_scores_gemma":[0.07927124,0.8249158,0.05994257,0.002668385,0.0004576521,0.03039353,0.002028665,0.00005069331,0.0002715396],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.157932,"threshold_uncertainty_score":0.8352343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9149103234974467,"score_gpt":0.7174708670495802,"score_spread":0.1974394564478665,"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."}}