{"id":"W2345616754","doi":"","title":"Assessing System Resilience and Ecosystem Services in Large River Basins: A Case Study of the Columbia River Basin","year":2013,"lang":"en","type":"article","venue":"Idaho law review","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Socio-Environmental Synthesis Center; National Science Foundation","keywords":"Ecosystem services; Provisioning; Corporate governance; Environmental resource management; Ecological resilience; Psychological resilience; Climate change; Resilience (materials science); Adaptive capacity; Drainage basin; Ecological systems theory; Geography; Ecosystem; Environmental planning; Environmental science; Business; Ecology; Computer 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":[0.001787293,0.0001336395,0.0004368372,0.00003065998,0.0006214876,0.0004139527,0.0004394657,0.00004405029,0.00005632421],"category_scores_gemma":[0.00001859791,0.0001072134,0.00006366858,0.0004837859,0.0002122453,0.0005940503,0.0001758967,0.0001162914,0.00002141444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001472027,"about_ca_system_score_gemma":0.00004294818,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2467662,"about_ca_topic_score_gemma":0.539191,"domain_scores_codex":[0.9968427,0.001521696,0.0005045841,0.0003343912,0.0004809648,0.0003156802],"domain_scores_gemma":[0.999083,0.00008654784,0.0002300171,0.0004342692,0.00008834163,0.00007777094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005799929,0.00126044,0.7308789,0.05337404,0.0001735538,0.001197197,0.1796655,0.00001940733,0.00001267346,0.01405858,0.0005111169,0.01884284],"study_design_scores_gemma":[0.002230802,0.0001587337,0.2914145,0.04292484,0.0005278951,0.0002056058,0.2140734,0.0003217404,0.000004099177,0.0001430082,0.4472092,0.0007861729],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873852,0.004763282,0.000004481642,0.0003238204,0.00009493165,0.003174864,0.00001009106,0.00003844934,0.004204856],"genre_scores_gemma":[0.9989468,0.0004187495,0.00005151106,0.0003681923,0.00002062307,0.0000895864,3.476608e-7,0.00001167562,0.00009251168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4466981,"threshold_uncertainty_score":0.7582496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846839089136723,"score_gpt":0.2896810255695051,"score_spread":0.2712126346781379,"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."}}