{"id":"W2302413818","doi":"10.2307/20159732","title":"Team diversity and information use","year":2005,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Team Dynamics and Performance","field":"Psychology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Diversity (politics); Categorization; Information integration; Knowledge management; Psychology; Computer science; Sociology; 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":[0.004666868,0.0002156359,0.0005562927,0.002415152,0.002101158,0.007406936,0.0004347691,0.00103741,0.02025128],"category_scores_gemma":[0.04395016,0.0002913775,0.0003131223,0.001886619,0.001746111,0.002974442,0.003465085,0.001002752,0.0014484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000874,"about_ca_system_score_gemma":0.0007812064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00295157,"about_ca_topic_score_gemma":0.001933931,"domain_scores_codex":[0.9957979,0.002179551,0.0001625745,0.00051113,0.0008354945,0.0005132642],"domain_scores_gemma":[0.9121173,0.06437238,0.00750036,0.002272376,0.004231317,0.009506161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001681458,0.001936772,0.6984996,0.0003915469,0.0005536441,0.0006723271,0.0959556,0.002223949,0.003985326,0.03682965,0.007655646,0.1496145],"study_design_scores_gemma":[0.00009265335,0.0004139861,0.9201127,0.0001651364,0.000112565,0.0003504188,0.04165627,0.00218846,0.0005470639,0.02318094,0.01112475,0.00005482006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572153,0.0007066315,0.000919378,0.001357524,0.00003366062,0.00002486418,0.0001260539,0.00001061306,0.03960593],"genre_scores_gemma":[0.9971205,0.0001613699,0.0001174677,0.0000416151,0.0000310613,0.00001649595,0.00002993253,0.000007935265,0.002473691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02025128,"threshold_uncertainty_score":0.06774724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784423924905777,"score_gpt":0.2411517990704286,"score_spread":0.2233075598213708,"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."}}