{"id":"W1971360980","doi":"10.4018/jcini.2011100101","title":"Cognitive Informatics and Cognitive Computing in Year 10 and Beyond","year":2011,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; McMaster University; University of New Brunswick; University of Alberta; University of Calgary","funders":"","keywords":"Cognitive computing; Informatics; Computer science; Cognition; Engineering informatics; Data science; Cognitive models of information retrieval; Information science; LIDA; Business informatics; Cognitive science; Field (mathematics); Artificial intelligence; Health informatics; Cognitive architecture; Psychology; Library science; Medicine; Engineering","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":[0.006753211,0.0007970827,0.0007705259,0.001779435,0.005554672,0.01447665,0.001192271,0.006080559,0.012801],"category_scores_gemma":[0.00685855,0.0003310037,0.0006111862,0.002405203,0.008435526,0.01268198,0.005844641,0.01181989,0.001653431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005863181,"about_ca_system_score_gemma":0.007154705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004409052,"about_ca_topic_score_gemma":0.006832987,"domain_scores_codex":[0.9962711,0.001236859,0.0001403832,0.0003567797,0.0009133717,0.001081434],"domain_scores_gemma":[0.9947865,0.001687239,0.0003185008,0.0003267616,0.0007680609,0.002112805],"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":[0.0001020667,0.000107539,0.0009706368,0.0001723301,0.00001347165,0.0002268071,0.004406601,0.0002048289,0.000399368,0.7639429,0.1741382,0.0553153],"study_design_scores_gemma":[0.00000710722,0.00007209562,0.00191918,0.0003733034,0.000005407016,0.0001603167,0.002990843,0.0001104877,0.0001574045,0.12698,0.8671862,0.00003758981],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03103704,0.1480448,0.007768581,0.4105913,0.09296244,0.0001222039,0.0003383975,0.0001618164,0.3089734],"genre_scores_gemma":[0.4996184,0.08552574,0.006520538,0.1045959,0.04266316,0.0003715496,0.000617195,0.0002223843,0.2598651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01447665,"threshold_uncertainty_score":0.04282355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02401358720108825,"score_gpt":0.2885988436030293,"score_spread":0.264585256401941,"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."}}