{"id":"W3127332941","doi":"10.22545/2021/00152","title":"Intergenerative Transdisciplinarity in “Glocal” Learning and Collaboration","year":2021,"lang":"en","type":"article","venue":"Transdisciplinary Journal of Engineering & Science","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Transdisciplinarity; Flourishing; Scholarship; Context (archaeology); Glocalization; Sociology; Face (sociological concept); Coronavirus disease 2019 (COVID-19); Work (physics); Political science; Pandemic; Globalization; Social science; Geography; Psychology; Engineering; Social psychology","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":[0.005874366,0.0001940469,0.0004396822,0.001027154,0.0003800354,0.0005865794,0.0006544134,0.00006009818,0.00007329392],"category_scores_gemma":[0.001378852,0.0001568107,0.0001009272,0.005413444,0.0003035176,0.002210804,0.0001937926,0.0006287154,0.000006307836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001840957,"about_ca_system_score_gemma":0.001013068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.750562e-7,"about_ca_topic_score_gemma":0.0002103481,"domain_scores_codex":[0.9959154,0.0002275509,0.001089209,0.0004877419,0.001834449,0.0004456554],"domain_scores_gemma":[0.9967714,0.0004515284,0.0002331844,0.0002271197,0.002008955,0.0003077887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000884391,0.0005723347,0.01822287,0.00008815539,0.0000517623,0.001540105,0.1039981,0.3271887,0.5295365,0.007008711,0.0002141646,0.01069414],"study_design_scores_gemma":[0.005166639,0.003695014,0.2030216,0.001050502,0.0000674306,0.002152155,0.1742899,0.4497086,0.1357547,0.02153157,0.002100042,0.00146189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690471,0.0008725088,0.02571531,0.003089697,0.0005541133,0.0001111046,0.000005104665,0.00001306786,0.0005919376],"genre_scores_gemma":[0.9959171,0.00007823862,0.003576936,0.000009276483,0.000118047,0.000004513523,0.000001310789,0.00001130635,0.0002832319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3937819,"threshold_uncertainty_score":0.6394554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224832910825796,"score_gpt":0.3873327429381628,"score_spread":0.3550844138299048,"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."}}