{"id":"W6947915476","doi":"10.4224/40001806","title":"Applied AI ethics: report 2019","year":2019,"lang":"en","type":"report","venue":"NPARC","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Applications of artificial intelligence; Best practice; Ethical issues","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01210286,0.001408544,0.0006854045,0.003416371,0.003734351,0.009292841,0.00265058,0.009505208,0.04568018],"category_scores_gemma":[0.01667857,0.0009328701,0.0009278773,0.0030412,0.001546931,0.003407705,0.003906116,0.007420284,0.05016306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01245491,"about_ca_system_score_gemma":0.04658879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09509192,"about_ca_topic_score_gemma":0.08086918,"domain_scores_codex":[0.9869401,0.001397709,0.0005826862,0.0005387099,0.008885145,0.001655654],"domain_scores_gemma":[0.9894105,0.002030764,0.0004413676,0.0006011975,0.00612579,0.001390428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002809727,0.00007003111,0.0002389047,0.0001038079,0.000003698662,0.00007628233,0.00008435081,0.0001059899,0.0001106699,0.009607146,0.9831374,0.006433601],"study_design_scores_gemma":[0.00001141861,0.000008988531,0.001201151,0.0001211535,0.000003415858,0.00004266731,0.0001039775,0.00009158636,0.0003225218,0.001187238,0.9968932,0.00001273293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.003068881,0.006100109,0.002504638,0.0619896,0.01133791,0.001945412,0.07671625,0.001562074,0.8347751],"genre_scores_gemma":[0.008030975,0.004163648,0.003850782,0.015281,0.001170985,0.002824553,0.0472194,0.0005857521,0.9168729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09509192,"threshold_uncertainty_score":0.1890769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06162455532630811,"score_gpt":0.3206378131793425,"score_spread":0.2590132578530344,"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."}}