{"id":"W3089106845","doi":"10.1080/24705357.2020.1813057","title":"How to strengthen interdisciplinarity in ecohydraulics? Outcomes from ISE 2018","year":2020,"lang":"en","type":"article","venue":"Journal of Ecohydraulics","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Field (mathematics); Conversation; Face (sociological concept); Engineering ethics; Political science; Public relations; Interdisciplinarity; Sociology; Knowledge management; Social science; Computer science; Engineering","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":[0.0273674,0.0002892637,0.0004456275,0.001048232,0.00261932,0.006711659,0.001120648,0.001187348,0.00949662],"category_scores_gemma":[0.05187632,0.0001428347,0.0004852647,0.001590639,0.002556383,0.006065232,0.01142618,0.002791401,0.001602569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008203918,"about_ca_system_score_gemma":0.01505834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009329952,"about_ca_topic_score_gemma":0.02058331,"domain_scores_codex":[0.9878221,0.006431522,0.0007668483,0.0003661038,0.003021692,0.001591779],"domain_scores_gemma":[0.9594737,0.009839979,0.003559737,0.002319081,0.01357421,0.01123321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008213394,0.001134672,0.1496415,0.005412864,0.0001260848,0.001460939,0.2723682,0.00174373,0.003327361,0.04519157,0.07456741,0.4442042],"study_design_scores_gemma":[0.00008800597,0.0004782519,0.1922472,0.003131472,0.00004654213,0.0003018506,0.4434717,0.0005121576,0.002356006,0.01477822,0.342497,0.00009182365],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.7153418,0.002439079,0.008337565,0.102908,0.0009750943,0.0005993813,0.00202742,0.0003084418,0.1670631],"genre_scores_gemma":[0.9822547,0.001283322,0.003348276,0.002430475,0.00009792166,0.0003268442,0.0008704073,0.0001081373,0.009279883],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.0273674,"threshold_uncertainty_score":0.1447344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03283214645572056,"score_gpt":0.2473964693144811,"score_spread":0.2145643228587605,"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."}}