{"id":"W2950955069","doi":"","title":"River system classifications and cumulative watershed perspectives to inform sustainable river basin management at global and regional scales","year":2019,"lang":"en","type":"article","venue":"","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental resource management; Context (archaeology); Sustainable management; Watershed management; Adaptive management; Multidisciplinary approach; Streamflow; Water resources; Scale (ratio); Sustainable development; Environmental planning; Temporal scales; Drainage basin; Environmental science; Watershed; Water resource management; Geography; Sustainability; Computer science; Ecology; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00541072,0.0006667751,0.0004617907,0.007839701,0.00172137,0.008335668,0.00128449,0.001023254,0.007929944],"category_scores_gemma":[0.009913675,0.0002570332,0.0005707809,0.008968121,0.008160944,0.01725713,0.004064683,0.002375735,0.0007436203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004337288,"about_ca_system_score_gemma":0.003004396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006988888,"about_ca_topic_score_gemma":0.01836235,"domain_scores_codex":[0.9965694,0.002087051,0.0002102486,0.0005092635,0.0004715986,0.0001523269],"domain_scores_gemma":[0.9928955,0.003882569,0.0007630393,0.001153261,0.000984638,0.0003208558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001193987,0.00001670124,0.009215477,0.0001933486,0.00002522652,0.00004691615,0.006880422,0.002869823,0.000334667,0.9166206,0.004968249,0.05881665],"study_design_scores_gemma":[0.000004955009,0.000027923,0.01125953,0.0005100543,0.00002860688,0.00008350463,0.01271387,0.006277681,0.0002355333,0.8028466,0.1659871,0.00002459514],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0844445,0.008896229,0.6762534,0.02485056,0.0009007617,0.0003826598,0.004109224,0.0005629017,0.1995998],"genre_scores_gemma":[0.6144572,0.00702481,0.3651503,0.001490969,0.000489763,0.0007128966,0.002637725,0.0002936588,0.007742661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008335668,"threshold_uncertainty_score":0.0314694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008778092569245893,"score_gpt":0.2206251232311581,"score_spread":0.2118470306619122,"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."}}