{"id":"W4251754534","doi":"10.1109/tcyb.2016.2559718","title":"IEEE Transactions on Cybernetics publication information","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Internet of Things and AI","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cybernet Systems Corporation (Canada)","funders":"","keywords":"Cybernetics; Computer science; Data science; World Wide Web; Library science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002633015,0.0003479309,0.0002335646,0.0004489419,0.0002925731,0.0004198427,0.0009934577,0.0002465432,0.0002746042],"category_scores_gemma":[0.00001188333,0.0002798486,0.0002318225,0.0004943944,0.00010802,0.001721626,0.000001777952,0.0004097114,0.001961813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002491341,"about_ca_system_score_gemma":0.0001003719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000644439,"about_ca_topic_score_gemma":0.00004167482,"domain_scores_codex":[0.9976366,0.00007903037,0.0006193947,0.0004557889,0.0007024314,0.0005067879],"domain_scores_gemma":[0.9980012,0.0002169786,0.0002275899,0.0009464387,0.000372129,0.0002356515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000840541,0.0007588206,0.000003156562,0.00003128086,0.000127217,0.000005041744,0.002047636,0.0129585,0.003081922,0.01642069,0.007494486,0.9569872],"study_design_scores_gemma":[0.004130268,0.002319004,0.0002907792,0.0004977757,0.0001669363,0.0001258103,0.0001160165,0.1441942,0.6654382,0.00500053,0.1756077,0.002112796],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003025658,0.000006962307,0.9830163,0.005362354,0.002313952,0.0003254632,0.00006320683,0.0004361576,0.005450014],"genre_scores_gemma":[0.9805843,0.0001296984,0.009137401,0.001849217,0.00007324488,0.00007804966,0.000002787511,0.00003117405,0.008114088],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9775587,"threshold_uncertainty_score":0.9999654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293533654914506,"score_gpt":0.2261962120202997,"score_spread":0.2132608754711546,"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."}}