{"id":"W2810380672","doi":"10.5751/es-10282-230248","title":"The network structure of multilevel water resources governance in Central America","year":2018,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of California, Davis","keywords":"Corporate governance; Network governance; Environmental resource management; Multi-level governance; Business; Geography; Environmental planning; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0006786508,0.00008170619,0.0001435792,0.002074929,0.0007656114,0.001417361,0.0003960081,0.0002534116,0.002103334],"category_scores_gemma":[0.005266855,0.0001638789,0.0001274099,0.002510922,0.001477309,0.001422721,0.001133022,0.0002718097,0.00007868902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002642527,"about_ca_system_score_gemma":0.001343356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09881749,"about_ca_topic_score_gemma":0.1502106,"domain_scores_codex":[0.9995961,0.0001199302,0.00001716625,0.000139584,0.00004949945,0.00007780029],"domain_scores_gemma":[0.9963897,0.001091995,0.001310311,0.0003009723,0.0005929014,0.0003139876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001295645,0.0001105932,0.8939306,0.00008733458,0.0001282483,0.0002199615,0.01136985,0.01355889,0.002200528,0.03609376,0.002969104,0.0392016],"study_design_scores_gemma":[0.00001174507,0.00003396777,0.9557986,0.00005636753,0.00003473611,0.0000917758,0.006681444,0.02062023,0.0002697914,0.01171885,0.004662165,0.00002036344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953376,0.0001162152,0.001227788,0.0002428529,0.000001986888,0.00001533645,0.0001954393,0.00001320996,0.002849439],"genre_scores_gemma":[0.9992929,0.00004043804,0.00033898,0.00001263497,0.000001257656,0.00000921197,0.00009503787,0.000001708528,0.0002079139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09881749,"threshold_uncertainty_score":0.1964846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006169730352648128,"score_gpt":0.2313725082927971,"score_spread":0.225202777940149,"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."}}