{"id":"W2964358315","doi":"10.1038/s41598-019-47292-4","title":"Critical Nodes in River Networks","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Centre for Applied Research in Cancer Control","keywords":"Betweenness centrality; Computer science; Context (archaeology); Drainage basin; Complex network; Network topology; Resilience (materials science); Centrality; Node (physics); Channel (broadcasting); Hydrology (agriculture); Environmental science; Computer network; Geology; Geography; Mathematics; Cartography; Statistics","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":[0.001167119,0.0003809415,0.0005295431,0.002687061,0.0009866257,0.001192523,0.0006654778,0.0006709411,0.002229188],"category_scores_gemma":[0.01009751,0.0003773535,0.0003813833,0.00130661,0.001837737,0.001972356,0.001073219,0.0006757488,0.0001937279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109706,"about_ca_system_score_gemma":0.0005350072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00228048,"about_ca_topic_score_gemma":0.002424289,"domain_scores_codex":[0.9994833,0.0001770791,0.00002967688,0.0001538868,0.00009788735,0.00005807393],"domain_scores_gemma":[0.9945254,0.003858623,0.0007060379,0.0002668232,0.0003938972,0.0002492437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001834334,0.0000507472,0.01709761,0.0003325292,0.0001126405,0.0004157942,0.0009943511,0.642805,0.007088249,0.2826906,0.002693319,0.04553582],"study_design_scores_gemma":[0.00003247451,0.00006329969,0.003561999,0.00006390004,0.00004074195,0.0003203533,0.000365513,0.6570801,0.002200632,0.3301381,0.006107135,0.00002576114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3880675,0.001427649,0.5996075,0.0005003087,0.00004848601,0.0001908429,0.0005671179,0.0003175019,0.009273104],"genre_scores_gemma":[0.9102769,0.0006585458,0.08691002,0.00006621602,0.00003762696,0.0001326265,0.000373111,0.00006998343,0.001474943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002687061,"threshold_uncertainty_score":0.007959723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006880731525194216,"score_gpt":0.2244566855843648,"score_spread":0.2175759540591706,"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."}}