{"id":"W2188720412","doi":"10.2166/wqrj.2009.010","title":"Developing Capacity for Large-Scale Rainwater Harvesting in Canada","year":2009,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Texas Water Development Board","keywords":"Rainwater harvesting; Impervious surface; Stormwater; Environmental planning; Surface runoff; Scale (ratio); Business; Environmental science; Environmental resource management; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007848614,0.0001290165,0.00018278,0.0001220271,0.000726633,0.0001714848,0.0004811205,0.00004162662,0.0005023921],"category_scores_gemma":[0.0001741672,0.0000951906,0.00006486822,0.0002411271,0.00007907016,0.0005132321,0.000241589,0.0005913526,0.00008819952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003765181,"about_ca_system_score_gemma":0.0001854601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5347409,"about_ca_topic_score_gemma":0.8709975,"domain_scores_codex":[0.996273,0.0005846506,0.0005060456,0.0003020931,0.0009748309,0.001359424],"domain_scores_gemma":[0.9993504,0.00009871831,0.00005200939,0.0002198283,0.0000555746,0.0002235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002958916,0.0004536677,0.8091756,0.0001422692,0.00009808396,0.0002348441,0.01657776,0.003363311,0.05142714,0.003076382,0.08639304,0.02876201],"study_design_scores_gemma":[0.002187895,0.0001464486,0.5778028,0.00009528527,0.000009527362,0.00006029144,0.001598917,0.001570051,0.01376756,0.03029291,0.3717878,0.0006804888],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9735532,0.000008659052,0.01340984,0.009906881,0.000126837,0.000382099,0.00001229446,0.00001507801,0.002585105],"genre_scores_gemma":[0.9823241,0.000004187149,0.01359867,0.0006150993,0.0001012558,0.00002080457,0.000007799621,0.00001144012,0.003316601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3362566,"threshold_uncertainty_score":0.9845817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1869446620038615,"score_gpt":0.3710365604391024,"score_spread":0.1840918984352409,"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."}}