{"id":"W2107501085","doi":"10.1007/s11368-009-0137-2","title":"Adaptive management frameworks for natural resource management at the landscape scale: implications and applications for sediment resources","year":2009,"lang":"en","type":"article","venue":"Journal of Soils and Sediments","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Adaptive management; Water Framework Directive; Natural resource management; Environmental resource management; Resource management (computing); Water resources; Natural resource; Process (computing); Sediment; Natural (archaeology); Environmental planning; Resource (disambiguation); Ecosystem management; Environmental science; Computer science; Business; Water quality; Ecology; Geography; Geology","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":[0.007535699,0.0009362343,0.0009508826,0.001663421,0.002210773,0.007177905,0.003458516,0.003131909,0.01108165],"category_scores_gemma":[0.01091019,0.0005216492,0.001144572,0.002515296,0.007380829,0.006725251,0.003942928,0.003204449,0.0004901541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005365247,"about_ca_system_score_gemma":0.005765771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01020094,"about_ca_topic_score_gemma":0.02507567,"domain_scores_codex":[0.997806,0.00123066,0.0001149048,0.0003049119,0.0003503893,0.0001930572],"domain_scores_gemma":[0.9952939,0.002311095,0.0005596442,0.0003403639,0.0007981246,0.0006968221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001502345,0.00008452603,0.001221611,0.00005901611,0.00005335593,0.00007686001,0.0005383924,0.05692882,0.000141453,0.9222113,0.002201854,0.01646778],"study_design_scores_gemma":[0.00002060977,0.00002531528,0.0009414333,0.00006405343,0.00003475089,0.00003774071,0.000925407,0.08876967,0.00005473104,0.903344,0.005758504,0.00002373904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03913372,0.002323216,0.8621458,0.03013851,0.0004412066,0.0002194715,0.0002684,0.0002428325,0.06508683],"genre_scores_gemma":[0.7688544,0.001709523,0.2218505,0.00115129,0.0003741588,0.0004995823,0.0001510051,0.00007177767,0.005337899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01108165,"threshold_uncertainty_score":0.03985304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007123606855672929,"score_gpt":0.2352053013181367,"score_spread":0.2280816944624638,"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."}}