{"id":"W1538316566","doi":"10.5772/39470","title":"Case Studies of Canadian Environmental Decision Support Systems","year":2010,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Decision support system; Business; Environmental planning; Computer science; Environmental science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002543505,0.0009383444,0.0004056235,0.00267114,0.007593876,0.003494618,0.00280448,0.001857299,0.007220762],"category_scores_gemma":[0.008408651,0.000373103,0.0008914919,0.008669258,0.002370438,0.00127356,0.001673851,0.001041323,0.00043804],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05761067,"about_ca_system_score_gemma":0.03553924,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9736884,"about_ca_topic_score_gemma":0.9823548,"domain_scores_codex":[0.996289,0.001153253,0.0001831599,0.0002367866,0.001280608,0.0008571359],"domain_scores_gemma":[0.9943936,0.002042029,0.0002089721,0.0003455028,0.002248087,0.0007616873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007141339,0.0008154301,0.06597775,0.001437509,0.0002621779,0.01184892,0.009920912,0.5686302,0.002213303,0.159606,0.07800126,0.1005724],"study_design_scores_gemma":[0.0006244878,0.0005255127,0.06656131,0.0005469738,0.0002519767,0.001143686,0.03531146,0.4052866,0.003486016,0.01753021,0.4683621,0.0003697444],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6921056,0.00192437,0.01568637,0.006114572,0.0001890649,0.001937847,0.009330651,0.0007571863,0.2719543],"genre_scores_gemma":[0.9378845,0.001711327,0.02677513,0.0003245675,0.00002708799,0.0005066009,0.004065265,0.0001103868,0.02859514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9423893,"threshold_uncertainty_score":0.4179966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02426954621490611,"score_gpt":0.2314332563548842,"score_spread":0.2071637101399781,"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."}}