{"id":"W2048450424","doi":"10.2478/s13230-010-0007-z","title":"Abstract intelligence and cognitive robots","year":2010,"lang":"en","type":"article","venue":"Paladyn Journal of Behavioral Robotics","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cognitive robotics; Computer science; Artificial intelligence; Robot; Artificial intelligence, situated approach; Cognition; Cognitive architecture; Human intelligence; Artificial general intelligence; Cognitive science; LIDA; Social intelligence; Embodied cognition; Human–computer interaction; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004994991,0.0001638398,0.0002463725,0.0001405302,0.000103119,0.0001955608,0.0004973106,0.00009835664,0.00001797786],"category_scores_gemma":[0.00008681817,0.0001444075,0.00009821202,0.0002247586,0.0001315207,0.0003501773,0.000192937,0.0008853503,0.00001301662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009992737,"about_ca_system_score_gemma":0.00008338019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005193839,"about_ca_topic_score_gemma":0.00001419702,"domain_scores_codex":[0.9987426,0.00003722111,0.0004462909,0.0002003589,0.000302758,0.0002707118],"domain_scores_gemma":[0.998349,0.0002924547,0.0003594259,0.0001677201,0.000585546,0.0002459259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002822887,0.0003863384,0.02046921,0.00001293972,0.00003277793,0.0004040185,0.0009339387,0.002927345,0.001916195,0.002621896,0.0001293872,0.9701377],"study_design_scores_gemma":[0.003337878,0.004206301,0.806934,0.002088495,0.0008472414,0.007647156,0.001380676,0.1303636,0.01652685,0.0232981,0.0005062636,0.002863443],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3572505,0.0002583256,0.6406118,0.0002202899,0.001345402,0.0000628749,0.00000115703,0.00002732256,0.0002223876],"genre_scores_gemma":[0.9468532,0.00005601433,0.05276425,0.00006451598,0.0002302826,3.6099e-7,5.383954e-7,0.00000999091,0.0000207957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9672742,"threshold_uncertainty_score":0.5888767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04014545503815824,"score_gpt":0.3109506430488143,"score_spread":0.270805188010656,"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."}}