{"id":"W3171997059","doi":"10.1186/s42862-021-00011-1","title":"Transdisciplinary training: what does it take to address today’s “wicked problems”?","year":2021,"lang":"en","type":"article","venue":"Innovation and Education","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Networks of Centres of Excellence of Canada","keywords":"Transdisciplinarity; Curriculum; Variety (cybernetics); Engineering ethics; Sociology; Ethos; Wicked problem; Paradigm shift; Knowledge management; Public relations; Pedagogy; Political science; Engineering; Social science; Computer science; Epistemology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001606644,0.0001364832,0.0001854054,0.0005917661,0.0003701731,0.001237876,0.0002428189,0.00008880879,0.000871008],"category_scores_gemma":[0.0009156179,0.0001011623,0.00003411137,0.004196857,0.00007909762,0.001672717,0.00009603798,0.0001463572,0.0001286017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006415531,"about_ca_system_score_gemma":0.0010836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003392125,"about_ca_topic_score_gemma":0.0004579032,"domain_scores_codex":[0.9974814,0.0001685184,0.0006848245,0.0005477403,0.0008575327,0.000259988],"domain_scores_gemma":[0.996572,0.0001879218,0.0001438553,0.0003822734,0.002576073,0.000137912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000190645,0.0005073507,0.0007055052,0.00004981544,0.00002827672,0.000006606605,0.1896869,0.00009716518,0.03304732,0.05407512,0.09434529,0.62726],"study_design_scores_gemma":[0.0005077555,0.0002602291,0.01362042,0.0002448669,0.00001032311,0.00003176984,0.6448672,0.0004900365,0.008991549,0.1330281,0.1975604,0.0003873335],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8671467,0.0001690716,0.001802585,0.1195393,0.001646731,0.0004092486,0.00001243213,0.00003285185,0.009241082],"genre_scores_gemma":[0.969331,0.00002480088,0.0007738158,0.002480901,0.0003737929,0.0001572606,0.0001479256,0.00001170694,0.0266988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6268727,"threshold_uncertainty_score":0.999799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1546721487360918,"score_gpt":0.4460905460585355,"score_spread":0.2914183973224437,"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."}}