{"id":"W2557723499","doi":"10.4018/ijcini.2016100101","title":"Cognitive Intelligence","year":2016,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; University of New Brunswick; University of Calgary","funders":"","keywords":"Cognitive computing; Computer science; Cognition; Big data; Field (mathematics); Informatics; Cognitive science; Artificial intelligence; Data science; Theme (computing); Deep learning; Set (abstract data type); World Wide Web; Psychology; Data mining; Programming language","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":[0.001509462,0.001208027,0.0006812694,0.002116931,0.001532156,0.007742726,0.001263118,0.001909086,0.03421155],"category_scores_gemma":[0.004801094,0.0002852018,0.0006764083,0.00151641,0.005048594,0.006391796,0.00320791,0.002442095,0.00957752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002621989,"about_ca_system_score_gemma":0.002432395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002698472,"about_ca_topic_score_gemma":0.002254365,"domain_scores_codex":[0.9986207,0.0003677067,0.00008650207,0.0003227656,0.0004871371,0.000115084],"domain_scores_gemma":[0.9984598,0.000512081,0.00008389979,0.0004017301,0.000387719,0.0001548326],"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":[0.0000197205,0.00002255191,0.000493596,0.0002485621,0.00003536155,0.00006931404,0.0008926879,0.0005264155,0.0002172294,0.8746805,0.0518248,0.07096919],"study_design_scores_gemma":[0.00000848615,0.00001604441,0.0006353706,0.000214363,0.00001330555,0.0001829576,0.0004098963,0.0005997081,0.0001827405,0.601707,0.3960139,0.00001614514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00439412,0.02308555,0.04432068,0.02003738,0.001541102,0.0001276702,0.0007789052,0.0005933685,0.9051213],"genre_scores_gemma":[0.5462904,0.04672353,0.07150713,0.01607639,0.00377994,0.0008041546,0.003333783,0.0005171949,0.3109676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03421155,"threshold_uncertainty_score":0.114449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024512866262602,"score_gpt":0.3028763641483745,"score_spread":0.2826312354857485,"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."}}