{"id":"W1979381021","doi":"10.1080/10643380500531171","title":"Risk Analysis Strategies in the Water Utility Sector: An Inventory of Applications for Better and More Credible Decision Making","year":2006,"lang":"en","type":"article","venue":"Critical Reviews in Environmental Science and Technology","topic":"Water Systems and Optimization","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Water Network; American Water Works Association Research Foundation","keywords":"Restructuring; Risk management; Risk analysis (engineering); Business; Asset (computer security); Competition (biology); Water utility; Finance; Water supply; Computer science; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0005834302,0.0000543362,0.0001344625,0.0001729384,0.00005544749,0.00002070622,0.0001141682,0.00004933929,0.000005128034],"category_scores_gemma":[0.00002124167,0.00003103884,0.00001363721,0.0003183852,0.0005383161,0.0001612355,0.00003318644,0.00006107992,3.737911e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002380682,"about_ca_system_score_gemma":0.000001911487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001562731,"about_ca_topic_score_gemma":0.0001406729,"domain_scores_codex":[0.999415,0.00001673002,0.0002055821,0.0001556106,0.00007749398,0.0001295166],"domain_scores_gemma":[0.9997949,0.00003112275,0.00001249725,0.0001459247,0.000003959955,0.00001158541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008874501,0.0003048468,0.7525347,0.0004736031,0.00001499422,0.000003023905,0.001082747,0.006202733,0.01621623,0.01244371,0.0000887835,0.2106257],"study_design_scores_gemma":[0.000621871,0.000202133,0.4565722,0.0002107546,0.0002414969,0.0000168117,0.003783852,0.3898977,0.006937123,0.1228032,0.01814611,0.0005667871],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.954376,0.001775614,0.0432955,0.00009419613,0.00001119564,0.0003492288,0.000007043881,0.00001058844,0.00008058964],"genre_scores_gemma":[0.9967402,0.0003293005,0.002800233,0.00001266577,0.000006315147,0.00010545,0.000003079756,0.000002250194,5.098116e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3836949,"threshold_uncertainty_score":0.1983448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285365003082734,"score_gpt":0.272396778059564,"score_spread":0.2595431280287367,"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."}}