{"id":"W3110514227","doi":"10.1021/acscentsci.0c01120","title":"Twelve Principles Trainees, PIs, Departments, and Faculties Can Use to Reduce Bias and Discrimination in STEM","year":2020,"lang":"en","type":"article","venue":"ACS Central Science","topic":"Career Development and Diversity","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Indigenous; Set (abstract data type); Immigration; Psychology; Face (sociological concept); Representation (politics); Cultural bias; Social psychology; Sociology; Political science; Social science; Computer science; Law; Politics","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":[0.0003347018,0.00006884992,0.00007810273,0.00005413038,0.000385794,0.000257882,0.0001818419,0.00002362029,0.000005123644],"category_scores_gemma":[0.0002879712,0.00006403746,0.000008611927,0.000515998,0.0003804773,0.0006245328,0.0001524654,0.00004239974,0.000001377108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474639,"about_ca_system_score_gemma":0.0001969549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003039816,"about_ca_topic_score_gemma":0.01592479,"domain_scores_codex":[0.9988618,0.00003705424,0.00009313134,0.0002750792,0.0003912999,0.0003416289],"domain_scores_gemma":[0.9995214,0.00003657689,0.00002841473,0.00004123221,0.00004145444,0.0003308584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001722363,0.00001703882,0.7726976,0.00001077493,0.000002296249,0.000007913861,0.207875,0.00001371308,0.001324065,0.007173465,0.000306953,0.01055399],"study_design_scores_gemma":[0.0001663655,0.00002094669,0.9708467,0.00001113847,0.000004217864,3.647568e-7,0.02140383,0.00004507141,0.001094504,0.00003861717,0.00624677,0.0001214427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939126,0.00003370339,0.00001278137,0.005225536,0.00007802871,0.0002437196,0.00001665818,0.00002337672,0.0004536375],"genre_scores_gemma":[0.9991075,0.00007536402,0.0002784618,0.0003123324,0.00002213035,0.000002538013,0.00000292663,0.000001750716,0.0001969395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1981492,"threshold_uncertainty_score":0.8886408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.169756343825415,"score_gpt":0.3014815382471959,"score_spread":0.1317251944217809,"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."}}