{"id":"W4311691392","doi":"10.5463/thesis.14","title":"Navigating Difference in Inter- &amp; Transdisciplinary Learning","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athena Sustainable Materials Institute","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Transdisciplinarity; Context (archaeology); Sustainability; Engineering ethics; Discipline; Stakeholder; Sociology; Stakeholder engagement; Interdisciplinarity; Knowledge management; Political science; Engineering; Public relations; Social science; Computer science; Geography","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":[0.03182823,0.0006745727,0.0008472505,0.002166641,0.008300849,0.01851568,0.003453437,0.00333925,0.007734319],"category_scores_gemma":[0.0309061,0.0005868266,0.001085452,0.001356616,0.01638202,0.01526008,0.03398768,0.005301492,0.001290896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004114438,"about_ca_system_score_gemma":0.008288019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001090438,"about_ca_topic_score_gemma":0.002395278,"domain_scores_codex":[0.9538289,0.03622436,0.0007268817,0.003269494,0.003034948,0.002915532],"domain_scores_gemma":[0.9693262,0.01853398,0.002158404,0.002859272,0.00201661,0.005105501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001193208,0.001463041,0.0150812,0.0008713225,0.0001036054,0.000773276,0.6775505,0.001590846,0.004007778,0.1315475,0.008427938,0.1584636],"study_design_scores_gemma":[0.0001316558,0.0004833923,0.006559615,0.0007913244,0.00004482294,0.0004592976,0.5919576,0.003944684,0.002153562,0.2136407,0.1797141,0.0001193135],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.743732,0.001533102,0.1173463,0.04210903,0.000579069,0.0009358049,0.0001183798,0.0003003307,0.09334593],"genre_scores_gemma":[0.9499539,0.0005270939,0.04039919,0.002885791,0.00006215694,0.0006867131,0.00007266481,0.00005983123,0.005352642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03182823,"threshold_uncertainty_score":0.1683258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08649856394225508,"score_gpt":0.4800575464585845,"score_spread":0.3935589825163294,"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."}}