{"id":"W2886895017","doi":"10.5539/cis.v11n3p102","title":"Identity Management Systems: Techno-Semantic Interoperability for Heterogeneous Federated Systems","year":2018,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Digital Rights Management and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Interoperability; Domain (mathematical analysis); Semantic interoperability; Identity (music); Representation (politics); Process (computing); Matching (statistics); Sketch; Legibility; Knowledge management; World Wide Web; Algorithm; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.00841435,0.0007283832,0.0007827798,0.002473228,0.002086091,0.009072237,0.002322881,0.003273059,0.003293064],"category_scores_gemma":[0.007879159,0.0006463249,0.00159208,0.003177627,0.00314572,0.01473765,0.006690794,0.004072348,0.00165076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002936116,"about_ca_system_score_gemma":0.00345933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003063321,"about_ca_topic_score_gemma":0.001439468,"domain_scores_codex":[0.9921839,0.002983695,0.0009420294,0.0008535089,0.002516652,0.0005200944],"domain_scores_gemma":[0.997476,0.0006262428,0.0002010929,0.001048558,0.0004997563,0.0001483326],"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":[0.00003978658,0.00005858156,0.0004285855,0.0002433864,0.00006111938,0.0002817958,0.0007197458,0.004169842,0.0018081,0.9173295,0.006141543,0.06871797],"study_design_scores_gemma":[0.00004306238,0.00006593639,0.0005299583,0.000486655,0.00007015679,0.0005248904,0.0006825855,0.07138049,0.005841303,0.6754602,0.2448381,0.00007663861],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00443669,0.002232744,0.95809,0.004273237,0.0005341467,0.0003472741,0.0001578525,0.001555652,0.02837232],"genre_scores_gemma":[0.2062495,0.005175082,0.7619926,0.001928124,0.0007808601,0.0009324265,0.001517058,0.0004612278,0.02096321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009072237,"threshold_uncertainty_score":0.04449981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453907235909566,"score_gpt":0.24790137480125,"score_spread":0.2333623024421543,"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."}}