{"id":"W2916773830","doi":"10.1007/s12652-019-01252-y","title":"A configurable identity matching algorithm for community care management","year":2019,"lang":"en","type":"article","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computational intelligence; Identity (music); Identity management; Matching (statistics); Algorithm; Artificial intelligence; Mathematics; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007605568,0.0001514783,0.0004436927,0.0003366216,0.0005710956,0.0008354479,0.001228891,0.00004048301,0.0001204781],"category_scores_gemma":[0.0001522635,0.0001216052,0.000190014,0.0002605839,0.00006363043,0.0008419312,0.0005714279,0.0003506769,0.00006029274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006787374,"about_ca_system_score_gemma":0.00002285514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008482551,"about_ca_topic_score_gemma":0.00003040951,"domain_scores_codex":[0.9970527,0.0002999311,0.001168184,0.0002362353,0.0009748857,0.000268103],"domain_scores_gemma":[0.9970176,0.0009180747,0.000869858,0.0004323945,0.0006636262,0.00009846835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007075139,0.0001831811,0.000268603,0.0002293692,0.0001640192,0.00001697156,0.01674422,0.001483227,0.0001115822,0.08072589,0.0009915244,0.8990107],"study_design_scores_gemma":[0.002371367,0.001676775,0.003276736,0.001061023,0.0002418733,0.0001011069,0.4583997,0.03077682,0.002080565,0.4285721,0.07065757,0.0007843245],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2791668,0.00028683,0.7172923,0.00008023644,0.0008508624,0.0003730041,0.000009609571,0.00001303724,0.001927237],"genre_scores_gemma":[0.9583561,0.00008970419,0.04036604,0.0004830468,0.0001067814,0.000001631544,0.000005940355,0.0000106412,0.0005800708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8982263,"threshold_uncertainty_score":0.8056244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1294250487522995,"score_gpt":0.4084695099433377,"score_spread":0.2790444611910382,"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."}}