{"id":"W43256554","doi":"","title":"Companion modeling and multi-agent systems for integrated natural resource management in Asia","year":2005,"lang":"en","type":"book","venue":"Agritrop (Cirad)","topic":"Water resources management and optimization","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Fund for Agricultural Development; Consortium of International Agricultural Research Centers; Centre de Coopération Internationale en Recherche Agronomique pour le Développement; Asian Institute of Technology; National Research Council of Thailand; Chulalongkorn University; Chiang Mai University; European Commission; International Development Research Centre","keywords":"Natural resource management; Indigenous; Natural resource; Dissemination; Business; Resource (disambiguation); Knowledge management; Political science; Environmental resource management; Geography; Computer science; Economics; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001662422,0.0004420604,0.0004492683,0.0004278237,0.00006557285,0.0001694614,0.0002369322,0.0002329676,0.000004491095],"category_scores_gemma":[0.000003192838,0.0004252728,0.00008966019,0.0001088423,0.00001946231,0.0001237417,0.00009868263,0.0003835783,0.00001356844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000454004,"about_ca_system_score_gemma":0.000006328883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002976263,"about_ca_topic_score_gemma":0.00004303603,"domain_scores_codex":[0.9984306,0.00003030191,0.0005139232,0.0004195455,0.0002173035,0.000388347],"domain_scores_gemma":[0.9995431,0.00002017023,0.00008069501,0.000253736,0.00003634736,0.00006595992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002522777,0.00002304087,0.00001043298,0.0009899641,0.000197293,0.00001510282,0.0002141738,0.9768698,0.000007540175,0.000861962,0.01497221,0.005813224],"study_design_scores_gemma":[0.0008600716,0.00001564586,0.00001992268,0.0004350618,0.0000855982,0.000002218291,0.0001461567,0.7794729,0.000002126036,0.00002482567,0.21857,0.0003654183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01063162,0.06385545,0.5849732,0.000271671,0.003927236,0.01561909,0.0002411468,0.0032002,0.3172804],"genre_scores_gemma":[0.2238366,0.005263939,0.02406452,0.0001221971,0.001608881,0.0006726403,0.006575142,0.0007138169,0.7371422],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5609087,"threshold_uncertainty_score":0.9998199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559179296327316,"score_gpt":0.2005243088491775,"score_spread":0.1849325158859043,"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."}}