{"id":"W2770070169","doi":"10.5942/jawwa.2017.109.0158","title":"The Spirit of a Water Professional","year":2017,"lang":"en","type":"article","venue":"American Water Works Association","topic":"Water resources management and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Natural disaster; Geography; Water source; Extreme weather; History; Oceanography; Water resource management; Environmental science; Geology; Meteorology; Climate change","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":[0.000268846,0.00007882292,0.0001073396,0.00003008323,0.0003380245,0.0001792645,0.0002270722,0.00003410977,0.00002596133],"category_scores_gemma":[0.00001723021,0.00004023931,0.00004377339,0.00002611041,0.00005218659,0.0001907018,0.00007616306,0.00009667924,0.00004684661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007090979,"about_ca_system_score_gemma":0.000001487073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004282339,"about_ca_topic_score_gemma":0.00002800064,"domain_scores_codex":[0.9993079,0.00002609005,0.0001618123,0.0000778444,0.0001848627,0.0002414571],"domain_scores_gemma":[0.9995822,0.00001993286,0.0001033932,0.0002330658,0.000041871,0.00001957375],"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":[0.0001722404,0.0001745343,0.5041745,0.00016569,0.001377016,0.000007717983,0.01508257,0.1526377,0.02075058,0.0005074217,0.05643171,0.2485183],"study_design_scores_gemma":[0.002081178,0.000176412,0.2850016,0.000263454,0.0002305235,8.458873e-7,0.001188652,0.1392485,0.1785129,0.001756451,0.3903683,0.001171113],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988194,0.00002446188,0.001217286,0.004327138,0.0006525305,0.0002037309,0.000001772068,0.0001115338,0.005267548],"genre_scores_gemma":[0.9956146,0.00004671865,0.0001085702,0.00002770198,0.000099626,0.00001705511,0.00002412089,0.00001647503,0.004045105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3339366,"threshold_uncertainty_score":0.2599846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003909609199006702,"score_gpt":0.2018066457192839,"score_spread":0.1978970365202772,"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."}}