{"id":"W4254158391","doi":"10.1109/thms.2017.2671618","title":"2017 IEEE International Conference on Systems, Man, and Cybernetics, October 5–8, 2017, Banff Center, Banff, Canada","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Human-Machine Systems","topic":"Advanced Data and IoT Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Center (category theory); Cybernetics; Library science; Geography; Computer science; Artificial intelligence; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001150653,0.000412547,0.0004225741,0.0001872362,0.0006566833,0.0003726006,0.0008121363,0.0001826931,0.0000454145],"category_scores_gemma":[0.00001090135,0.0003933667,0.00006264146,0.00003709857,0.000143573,0.00038594,0.000008361251,0.0005525941,0.0000455342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000288542,"about_ca_system_score_gemma":0.00004379626,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08692812,"about_ca_topic_score_gemma":0.1216019,"domain_scores_codex":[0.9982513,0.00003685722,0.0004653469,0.0004556982,0.0004036635,0.0003871017],"domain_scores_gemma":[0.9983974,0.00005655222,0.0001724487,0.001135743,0.00009870659,0.000139221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003161612,0.0009675199,0.001469897,0.002618037,0.002710626,0.0007877658,0.0007166203,0.6895703,0.0278241,0.02817106,0.2220139,0.02283402],"study_design_scores_gemma":[0.0104644,0.0009765846,0.004667527,0.004769246,0.0003782814,0.000839962,0.002134145,0.5953169,0.01752036,0.0003229181,0.3573024,0.005307308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2722113,0.004593387,0.4894876,0.001366721,0.08937301,0.004339143,0.01741652,0.004221969,0.1169904],"genre_scores_gemma":[0.9961454,0.0007904584,0.00005654279,0.00002276101,0.0001769893,0.00009150345,0.00006523645,0.00005789332,0.002593162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7239342,"threshold_uncertainty_score":0.9998518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06134236329312846,"score_gpt":0.303581919121339,"score_spread":0.2422395558282106,"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."}}