{"id":"W3169701557","doi":"","title":"Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources","year":2019,"lang":"en","type":"article","venue":"IEEE Conference Proceedings","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Identity (music); Computer science; Inference; Biometrics; Cognition; Process (computing); Identity management; Probabilistic logic; Artificial intelligence; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01101962,0.001133602,0.00105745,0.003324781,0.002424376,0.0132658,0.002403534,0.002811742,0.002744514],"category_scores_gemma":[0.03756446,0.0006819259,0.001320754,0.002251878,0.003756472,0.01533521,0.007758322,0.003325731,0.0004317941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004129261,"about_ca_system_score_gemma":0.002867632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006200519,"about_ca_topic_score_gemma":0.00366205,"domain_scores_codex":[0.9889833,0.005192938,0.0005424902,0.001170751,0.00353812,0.0005723264],"domain_scores_gemma":[0.9807487,0.01007071,0.003350751,0.002650463,0.002384305,0.0007950987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002710972,0.0002145285,0.008993294,0.0002536943,0.0003895228,0.0009226191,0.004266215,0.08310084,0.002117848,0.7716278,0.002416438,0.125426],"study_design_scores_gemma":[0.00002384273,0.0000830952,0.002031414,0.000209586,0.0001469485,0.0002770983,0.001957121,0.2703585,0.001665207,0.7162389,0.006888329,0.0001200261],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06567533,0.001422668,0.8924577,0.007938802,0.0001632101,0.0001934616,0.0001547951,0.0002298874,0.03176415],"genre_scores_gemma":[0.9227915,0.0006389115,0.073328,0.000327158,0.0001156429,0.00009727694,0.00008415728,0.00003595302,0.002581393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0132658,"threshold_uncertainty_score":0.05827802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06815269028137452,"score_gpt":0.306804426647157,"score_spread":0.2386517363657824,"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."}}