{"id":"W2942836536","doi":"10.1017/sus.2019.2","title":"Mobilizing transdisciplinary collaborations: collective reflections on <i>de</i>centering academia in knowledge production","year":2019,"lang":"en","type":"article","venue":"Global Sustainability","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"University of Cambridge; Inter-American Institute for Global Change Research; National Science Foundation","keywords":"Sustainability; Government (linguistics); Knowledge production; Public relations; Business; Collective responsibility; Political science; Production (economics); Knowledge management; Economics; Computer science; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.001079316,0.0001704444,0.0001991045,0.000184816,0.0004225777,0.00005748171,0.0001863996,0.0003142084,0.00002511642],"category_scores_gemma":[0.0005984204,0.0001816397,0.00004582099,0.003386151,0.0001400147,0.0005330396,0.0001572033,0.0005302717,0.00004027428],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004243592,"about_ca_system_score_gemma":0.0004308286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007571553,"about_ca_topic_score_gemma":0.0002418567,"domain_scores_codex":[0.998638,0.00005491693,0.000308745,0.0004736407,0.0001310805,0.0003936609],"domain_scores_gemma":[0.9991247,0.00002663384,0.0001001691,0.0002158574,0.0005240111,0.000008637952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005848015,0.001255075,0.5108758,0.0007864333,0.00005334059,0.000008917159,0.007594909,0.002339989,0.0002199071,0.467112,0.001682379,0.007486471],"study_design_scores_gemma":[0.0008836688,0.0000709848,0.5537628,0.00009958429,0.00001691231,0.000002713831,0.06350737,0.0006848504,0.0002386093,0.3669948,0.01325054,0.0004871452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9342678,0.00003447057,0.0002591143,0.003074398,0.0004947128,0.001330745,0.000002822577,0.0001950037,0.0603409],"genre_scores_gemma":[0.9986672,0.000003229646,0.0001661825,0.0002705191,0.0001679632,0.0002620975,0.00001071215,0.000009969531,0.0004421386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1001172,"threshold_uncertainty_score":0.999579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03195576590163085,"score_gpt":0.3258885496651138,"score_spread":0.293932783763483,"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."}}