{"id":"W1995182262","doi":"10.1016/j.landurbplan.2005.05.006","title":"Room for rivers: An integrative search strategy for floodplain restoration","year":2005,"lang":"en","type":"article","venue":"Landscape and Urban Planning","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Eidgenössische Anstalt für Wasserversorgung Abwasserreinigung und Gewässerschutz; University of British Columbia","keywords":"Floodplain; Restoration ecology; Environmental resource management; Flood myth; Inefficiency; Process (computing); Delphi method; Computer science; Environmental science; Ecology; Geography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00220256,0.000799087,0.001147815,0.00341573,0.001511778,0.003237885,0.001829172,0.001580209,0.01857531],"category_scores_gemma":[0.007043066,0.0004025401,0.0009576,0.002602335,0.0008251078,0.005886552,0.003380302,0.000694884,0.001932833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005537237,"about_ca_system_score_gemma":0.002863022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003310367,"about_ca_topic_score_gemma":0.01095863,"domain_scores_codex":[0.9989688,0.0004522581,0.00006491938,0.0002203205,0.0002025066,0.00009116495],"domain_scores_gemma":[0.9985144,0.0007518998,0.00009857683,0.0002599493,0.0002302292,0.0001449863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005106759,0.0004550965,0.008427637,0.0004311328,0.0001677895,0.0003704546,0.003696607,0.03214584,0.007277903,0.07325803,0.0300855,0.8431734],"study_design_scores_gemma":[0.0003765339,0.0008854512,0.01115192,0.0003695273,0.0009192562,0.0009472189,0.0206961,0.5892491,0.01309278,0.2642716,0.09775732,0.0002832693],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09803807,0.0006580323,0.8483716,0.003660877,0.000115169,0.0009304426,0.00108513,0.005786516,0.0413541],"genre_scores_gemma":[0.3379166,0.0003175688,0.6484072,0.0003119965,0.00003789067,0.0005309826,0.001021315,0.0006309653,0.01082548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01857531,"threshold_uncertainty_score":0.06214058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02663021751940318,"score_gpt":0.2798973391842151,"score_spread":0.2532671216648119,"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."}}