{"id":"W4399933970","doi":"10.1088/2515-7620/ad5b3f","title":"Developing a transdisciplinary tool for water risk management and decision-support in Ontario, Canada","year":2024,"lang":"en","type":"article","venue":"Environmental Research Communications","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Risk management; Stakeholder; Context (archaeology); Business; Environmental resource management; Normative; Private sector; Incentive; IT risk management; Risk analysis (engineering); Economics; Public relations; Finance; Political science; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01412257,0.0008735437,0.0005658932,0.005413789,0.005979868,0.005479807,0.00250883,0.0009526651,0.01443428],"category_scores_gemma":[0.03097454,0.0006411634,0.0009342004,0.006716087,0.001567915,0.002948402,0.004520794,0.001067062,0.001595506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06272152,"about_ca_system_score_gemma":0.1438269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9384469,"about_ca_topic_score_gemma":0.9643132,"domain_scores_codex":[0.9897708,0.003972478,0.001134291,0.0009589166,0.003249972,0.0009136316],"domain_scores_gemma":[0.9564092,0.01677368,0.001973822,0.002311442,0.0189187,0.003613152],"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":[0.0009446578,0.0007964837,0.07406929,0.002750633,0.000241591,0.002478533,0.08204026,0.02125206,0.009636267,0.03308112,0.1096727,0.6630365],"study_design_scores_gemma":[0.0003314397,0.0003132058,0.06504836,0.002201363,0.0002097503,0.0003684942,0.08654726,0.0973875,0.008555518,0.02074952,0.7176437,0.0006439075],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.3992209,0.002240464,0.2854407,0.02796751,0.0005814562,0.008291683,0.02597559,0.01040518,0.2398765],"genre_scores_gemma":[0.5175855,0.001477348,0.4366528,0.0009621956,0.00005113289,0.002695502,0.007535166,0.0004522923,0.03258804],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06272152,"threshold_uncertainty_score":0.4550786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04253610011583125,"score_gpt":0.3357272280817651,"score_spread":0.2931911279659339,"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."}}