{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005066824,0.00007731876,0.0002265298,0.00004941987,0.000690508,0.00002036601,0.0002521992,0.00005120919,0.0004009702],"category_scores_gemma":[0.00002713333,0.00006562137,0.0001027322,0.00008323148,0.0003802967,0.0001183825,0.00002899322,0.0004706596,0.000001185212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009293665,"about_ca_system_score_gemma":0.0003468438,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6202435,"about_ca_topic_score_gemma":0.8023182,"domain_scores_codex":[0.9988357,0.0001124032,0.0003045975,0.00007819529,0.0004792159,0.000189834],"domain_scores_gemma":[0.9993696,0.00005773025,0.0003175744,0.00007384684,0.00005545405,0.0001257555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.000167901,0.0004302362,0.2139794,0.0001847457,0.001675952,0.0006854092,0.3711921,0.0000125163,0.0005939171,0.3594238,0.03923509,0.01241895],"study_design_scores_gemma":[0.001196683,0.0001824137,0.5334551,0.0001709378,0.0002420338,0.000006006459,0.05252237,0.000003196162,0.0002399825,0.05551539,0.3561693,0.0002965243],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.925568,0.0001070279,0.00001049465,0.004232839,0.0004165579,0.00005018671,0.000006572838,0.000005800722,0.06960246],"genre_scores_gemma":[0.9987493,0.0001403933,0.0003269892,0.00007451351,0.0003746775,3.139502e-7,5.817952e-7,0.000005242882,0.0003279611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3194757,"threshold_uncertainty_score":0.5310899,"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."}}