{"id":"W7098556775","doi":"","title":"Research Article An Algorithm Using Administrative Data to Identify Patient Attachment to a Family Physician","year":2015,"lang":"en","type":"article","venue":"","topic":"Historical and Literary Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Proxy (statistics); Population; Patient data; Data collection; Health services research; Information system; Medical information; Medical record","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":[0.008678298,0.001378286,0.001977338,0.007006532,0.001918218,0.003573007,0.002825164,0.001860361,0.005881821],"category_scores_gemma":[0.02501831,0.0007559097,0.002195107,0.004857659,0.0006817643,0.001553185,0.002405504,0.001597158,0.002190533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002712459,"about_ca_system_score_gemma":0.008573378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01880788,"about_ca_topic_score_gemma":0.01553902,"domain_scores_codex":[0.9940598,0.001987022,0.001227024,0.001407711,0.0009798281,0.0003385311],"domain_scores_gemma":[0.9895576,0.005127723,0.0008561125,0.0006141408,0.003543699,0.0003008905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001292348,0.001240939,0.2230841,0.0006198412,0.001091732,0.0006114921,0.0005175804,0.06490499,0.003720829,0.005240532,0.02005888,0.6776168],"study_design_scores_gemma":[0.000810357,0.000412626,0.03606415,0.0002343023,0.0004826663,0.001514912,0.0005586187,0.9368961,0.00458672,0.007262096,0.01105115,0.0001263538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1291075,0.0005963641,0.8457296,0.001918977,0.0002702893,0.006413381,0.006008624,0.00576294,0.004192394],"genre_scores_gemma":[0.1280137,0.0001269088,0.8636226,0.0001893903,0.00006923332,0.002034917,0.004502899,0.00009498643,0.001345273],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01880788,"threshold_uncertainty_score":0.04589581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5266414553563574,"score_gpt":0.5451780240472593,"score_spread":0.01853656869090192,"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."}}