{"id":"W2004131391","doi":"10.5465/amj.2005.19573112","title":"Team Diversity and Information Use","year":2005,"lang":"en","type":"article","venue":"Academy of Management Journal","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":753,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Diversity (politics); Categorization; Information integration; Knowledge management; Information processing; Information system; Psychology; Social psychology; Sociology; Computer science; Political science; Cognitive psychology; Data mining; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.005207676,0.0002846229,0.0003761926,0.002989729,0.002142175,0.004357714,0.0004787294,0.0006152006,0.003757969],"category_scores_gemma":[0.03339741,0.0001811567,0.0005234463,0.001691135,0.001876268,0.002341078,0.005094199,0.0008198867,0.0002276748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072137,"about_ca_system_score_gemma":0.001287482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003025397,"about_ca_topic_score_gemma":0.002874946,"domain_scores_codex":[0.9920879,0.00427527,0.0006267957,0.000527121,0.00158379,0.0008991493],"domain_scores_gemma":[0.9532205,0.02965089,0.0080332,0.002149853,0.002677385,0.004268219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002391908,0.0003699594,0.8746824,0.0001917873,0.0002458822,0.0003364295,0.0439855,0.0007047508,0.001367205,0.004778421,0.0005654036,0.0725332],"study_design_scores_gemma":[0.000050401,0.0005051594,0.925739,0.0003195394,0.0001210153,0.0005660177,0.05144843,0.00219225,0.001029547,0.01028458,0.007676006,0.00006811105],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833144,0.0003935876,0.001703999,0.0005636344,0.00001744895,0.00002829191,0.0000643205,0.000009570935,0.01390473],"genre_scores_gemma":[0.9991925,0.00006789465,0.0003504314,0.00003054621,0.00001127558,0.0000124712,0.00002547504,0.00000210982,0.0003071536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005207676,"threshold_uncertainty_score":0.02754116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1000808747153825,"score_gpt":0.2938984386717342,"score_spread":0.1938175639563517,"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."}}