{"id":"W3150425792","doi":"10.3758/s13428-021-01592-8","title":"The good and the bad: Are some attribute words better than others in the Implicit Association Test?","year":2021,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Psychology; Implicit-association test; Cognitive psychology; Set (abstract data type); Test (biology); Quality (philosophy); Selection (genetic algorithm); Association (psychology); Social psychology; Artificial intelligence; Computer science","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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.03244005,0.0001027851,0.0002011811,0.00005774546,0.001766269,0.0004604647,0.0007348122,0.0001994547,0.00009125215],"category_scores_gemma":[0.006443675,0.0000533109,0.000117464,0.0009357802,0.0009565249,0.000141837,0.0001726943,0.0009360116,0.00001685838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002574078,"about_ca_system_score_gemma":0.000141567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002999152,"about_ca_topic_score_gemma":0.006618229,"domain_scores_codex":[0.9827784,0.0150515,0.0002461254,0.0002948147,0.0008869379,0.0007422276],"domain_scores_gemma":[0.9861537,0.01304242,0.0001084953,0.0003659721,0.0002555772,0.00007388608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005121811,0.000224616,0.7757518,0.000003718171,0.00004231143,0.00003106332,0.05481441,5.039652e-8,0.001995749,0.02203522,0.008601987,0.1364478],"study_design_scores_gemma":[0.0006215977,0.00004381761,0.818809,0.00001434512,0.00002169801,0.000002695248,0.06806695,0.000002519957,0.0001750346,0.01744083,0.09469868,0.0001028242],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8277771,0.001447035,0.00008786854,0.1618251,0.000601268,0.000958493,0.00001921296,0.00002984733,0.00725412],"genre_scores_gemma":[0.9800214,0.001756424,0.0009979005,0.002644414,0.00134394,0.001267648,0.000005452454,0.00003510518,0.01192772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1591807,"threshold_uncertainty_score":0.9995333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1925070559075074,"score_gpt":0.5669183079270538,"score_spread":0.3744112520195464,"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."}}