{"id":"W4211017739","doi":"10.1038/s41586-019-1138-y","title":"Machine behaviour","year":2019,"lang":"en","type":"review","venue":"Nature","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1165,"is_retracted":false,"has_abstract":false,"ca_institutions":"Google (Canada); University of British Columbia; Canadian Institute for Advanced Research","funders":"Army Research Office; NIH Office of the Director; Intelligence Advanced Research Projects Activity; Defense Advanced Research Projects Agency; Companhia Brasileira de Metalurgia e Mineração; Agence Nationale de la Recherche; Future of Life Institute; Max-Planck-Gesellschaft; Deutsche Forschungsgemeinschaft; National Science Foundation; Office of the Director of National Intelligence; Robert Wood Johnson Foundation; Office of Naval Research","keywords":"Field (mathematics); Control (management); Politics; Set (abstract data type); Computer science; Artificial intelligence; Engineering ethics; Management science; Data science; Political science; Engineering; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005641187,0.000612719,0.0006025275,0.001263828,0.0004613989,0.002931174,0.0009746297,0.002159561,0.01856205],"category_scores_gemma":[0.002544841,0.0002155335,0.0003492934,0.001161553,0.002753935,0.002364695,0.001074013,0.001262147,0.005534073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001088309,"about_ca_system_score_gemma":0.001418662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001200823,"about_ca_topic_score_gemma":0.001403452,"domain_scores_codex":[0.9993174,0.0002348141,0.00003878081,0.0001424398,0.0002113437,0.00005520986],"domain_scores_gemma":[0.9991672,0.0004649779,0.00007911331,0.0001325687,0.0001143242,0.0000418255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005326225,0.00005715917,0.0005618344,0.004291157,0.00007822245,0.000119442,0.0004365978,0.001322677,0.001675383,0.373662,0.05060084,0.5671415],"study_design_scores_gemma":[0.00001131166,0.00004021445,0.001195641,0.001497207,0.00003388835,0.0004240042,0.0001479811,0.00075166,0.0009253233,0.1344017,0.860547,0.00002396079],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005126673,0.6041076,0.03628615,0.01449199,0.003650258,0.0001035962,0.0004728762,0.0004044412,0.3353564],"genre_scores_gemma":[0.214034,0.6055719,0.01504461,0.00800819,0.003510805,0.0003257114,0.0008398716,0.0001537069,0.1525113],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9995386,"threshold_uncertainty_score":0.06209624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08928312167698203,"score_gpt":0.4883792151839298,"score_spread":0.3990960935069478,"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."}}