{"id":"W2595013643","doi":"10.18260/1-2--22892","title":"Optimizing Linguistic Diversity in Highly Multicultural Engineering Design Teams","year":2020,"lang":"en","type":"article","venue":"","topic":"Design Education and Practice","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multiculturalism; Diversity (politics); Psychology; Cultural diversity; Cognition; Cognitive style; Knowledge management; Engineering; Pedagogy; Sociology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004795873,0.0003891262,0.0002922353,0.001301751,0.002575702,0.00312178,0.0007914648,0.0005668546,0.003004403],"category_scores_gemma":[0.01444143,0.0002151795,0.0003288967,0.0004902044,0.001194189,0.001045734,0.004644285,0.0006057365,0.0003234936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104198,"about_ca_system_score_gemma":0.001224499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001932931,"about_ca_topic_score_gemma":0.003099603,"domain_scores_codex":[0.9957002,0.002276498,0.0002879368,0.0003585455,0.0009006719,0.0004761413],"domain_scores_gemma":[0.983434,0.005171446,0.005403163,0.0009722505,0.002233396,0.002785718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005299563,0.002315569,0.8855185,0.0001155042,0.00009213608,0.0007418559,0.02952604,0.002401066,0.007961738,0.0008804507,0.0006000671,0.06931709],"study_design_scores_gemma":[0.0001066958,0.001879156,0.9095837,0.0001449728,0.00006907299,0.0006293232,0.0658739,0.009150344,0.004739902,0.004347897,0.003388949,0.00008604539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980357,0.00001895642,0.0005480316,0.0000509754,0.000003445471,0.0000133217,0.0000050249,0.000003706656,0.001320787],"genre_scores_gemma":[0.9990767,0.000008489436,0.0006233138,0.00002660491,0.000003427917,0.0000192447,0.000008135687,0.00000167071,0.0002323297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004795873,"threshold_uncertainty_score":0.02536333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03947309788372064,"score_gpt":0.234604736049481,"score_spread":0.1951316381657604,"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."}}