{"id":"W4231563625","doi":"10.4018/978-1-7998-2460-2.ch005","title":"Abstract Intelligence","year":2020,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Cognitive computing; Cognition; Informatics; Cognitive robotics; Computer science; Cognitive science; Computational intelligence; Set (abstract data type); Artificial intelligence; Embodied cognition; Data science; Psychology; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001097755,0.0004331155,0.0003940374,0.00004207069,0.0001070261,0.000235578,0.001425115,0.000301797,0.00002817376],"category_scores_gemma":[0.00002450826,0.000446389,0.000256762,0.00003523186,0.00008349483,0.00005374084,0.000817112,0.000564643,0.001319481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001115326,"about_ca_system_score_gemma":0.0001939243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000112461,"about_ca_topic_score_gemma":0.000009726386,"domain_scores_codex":[0.9980145,0.00001232765,0.0003805576,0.0008438966,0.0003999702,0.0003488204],"domain_scores_gemma":[0.998651,0.0001000706,0.0002178555,0.0006246414,0.0001494827,0.0002569022],"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":[0.000004249279,0.000003000875,9.625236e-7,0.00001224988,0.00003073144,0.0001622968,0.00002534677,0.000009380568,0.000001209816,0.754949,0.003028185,0.2417734],"study_design_scores_gemma":[0.00008208032,0.0000935251,0.00004101381,0.000408197,0.00002303342,0.00005428253,0.000001938198,0.002548892,0.0000563362,0.9349385,0.06107685,0.000675351],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00000287965,0.0004705197,0.1635681,0.0001797355,0.0008182928,0.0001501698,0.00001709022,0.000445359,0.8343478],"genre_scores_gemma":[0.9167038,0.00003173989,0.01100342,0.00519851,0.002137209,0.00001080657,0.000006580231,0.00008977384,0.06481817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9167009,"threshold_uncertainty_score":0.9997988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03324681350062855,"score_gpt":0.25679314697858,"score_spread":0.2235463334779515,"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."}}