{"id":"W2003094035","doi":"10.3316/jhs0603061","title":"Learning from Canada: Russian Basin Management of Transboundary Rivers","year":2010,"lang":"en","type":"article","venue":"Journal of Human Security","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"State (computer science); Drainage basin; Structural basin; Resource (disambiguation); Politics; Political science; Environmental resource management; Geography; Law; Environmental science","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":[0.001019459,0.000294311,0.0001961295,0.0005097154,0.008706762,0.003350183,0.0007363292,0.001177411,0.02154934],"category_scores_gemma":[0.001584991,0.0001488853,0.0002072903,0.0009759333,0.001761732,0.001418344,0.003347171,0.001715209,0.001482482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02233438,"about_ca_system_score_gemma":0.09004489,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9197127,"about_ca_topic_score_gemma":0.9761335,"domain_scores_codex":[0.9991723,0.0001634895,0.00001837912,0.00005639979,0.0002916854,0.0002977563],"domain_scores_gemma":[0.9986786,0.0000852623,0.00006323093,0.00003149207,0.0004973432,0.0006439399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006823908,0.0001649748,0.02081419,0.0004216089,0.00002825941,0.0008844096,0.02861874,0.002079456,0.001571513,0.04720424,0.4790846,0.4190598],"study_design_scores_gemma":[0.0000102584,0.00004479475,0.03493525,0.0004664428,0.00001747597,0.0001980745,0.03909611,0.0005384039,0.000567139,0.003425521,0.9206615,0.00003906863],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.133467,0.02338814,0.003952466,0.16847,0.001711018,0.0002209321,0.0006725577,0.0003446972,0.6677732],"genre_scores_gemma":[0.7020448,0.02633247,0.005139922,0.0079234,0.0002375723,0.00007745082,0.000572518,0.0001370042,0.2575349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08028728,"threshold_uncertainty_score":0.162048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476295406496868,"score_gpt":0.2835950937950208,"score_spread":0.2688321397300522,"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."}}