{"id":"W2201096852","doi":"10.4018/ijssci.2015040103","title":"Cognitive Informatics and Computational Intelligence","year":2015,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of New Brunswick; University of Calgary","funders":"","keywords":"Cognitive computing; Computer science; Informatics; Cognition; LIDA; Multidisciplinary approach; Computational intelligence; Data science; Cognitive science; Field (mathematics); Information science; Engineering informatics; Artificial intelligence; Health informatics; Cognitive model; Psychology; Sociology; Social science; Library science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002059701,0.0002079944,0.0002384367,0.000642647,0.0002264834,0.0007500401,0.001389615,0.00005658486,0.000006333897],"category_scores_gemma":[0.001650612,0.0001893405,0.00005931805,0.0008288236,0.0009376908,0.002007121,0.0007269327,0.000329289,0.00001992434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001429162,"about_ca_system_score_gemma":0.001128942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000966006,"about_ca_topic_score_gemma":0.000001401158,"domain_scores_codex":[0.9964132,0.00006201775,0.000832065,0.0003113959,0.002095502,0.0002858435],"domain_scores_gemma":[0.9893213,0.001101118,0.0005727949,0.0001038597,0.008487158,0.0004137807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006645892,0.0001097666,0.00247614,0.000009985219,0.00007329006,0.00006389988,0.004256737,0.2000983,0.000002737809,0.04041936,0.0002424724,0.7521809],"study_design_scores_gemma":[0.0003570861,0.0004007001,0.004107175,0.0003115665,0.00001595,0.001936537,0.00162574,0.7810249,0.0002281385,0.2092647,0.0003920184,0.0003354783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0309528,0.000524372,0.9663913,0.0006626376,0.00100629,0.00009440989,0.000007201605,0.00004816736,0.0003128054],"genre_scores_gemma":[0.793583,0.00008325142,0.205167,0.000995867,0.0001460459,0.000001880174,0.00000367907,0.000005876582,0.00001340977],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7626302,"threshold_uncertainty_score":0.772108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04427897386390939,"score_gpt":0.3268779665015775,"score_spread":0.2825989926376681,"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."}}