{"id":"W2998725312","doi":"10.1002/9781119300762.wsts0168","title":"Optimization for Booster Chlorination","year":2019,"lang":"en","type":"other","venue":"Encyclopedia of Water","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Booster (rocketry); Chlorine; Odor; Haloacetic acids; Residual; Trihalomethane; Environmental science; Computer science; Water treatment; Waste management; Environmental engineering; Chemistry; Engineering; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005353806,0.000175216,0.0002372247,0.0001856467,0.00000831981,0.00001294834,0.00009080738,0.0002313737,0.0005614872],"category_scores_gemma":[0.000003139329,0.0001330987,0.00006081329,0.00003251221,0.000007603039,0.00007137067,0.00001469699,0.00004580312,0.0001083786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002264153,"about_ca_system_score_gemma":0.000005152418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001522982,"about_ca_topic_score_gemma":0.0000162767,"domain_scores_codex":[0.9993604,0.000007088001,0.0002278571,0.000144477,0.0001009999,0.0001591664],"domain_scores_gemma":[0.9996862,0.000007023176,0.00005174269,0.0001988088,0.00003451927,0.00002171319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004073504,0.00000813852,0.00002006027,0.0008747765,0.00005064238,2.538078e-7,0.0002434262,0.2429461,0.00001584551,0.00003776238,0.7553979,0.000401027],"study_design_scores_gemma":[0.0003090112,0.00002340149,0.000003039032,0.0001093345,0.00002725424,4.729874e-7,0.000005139148,0.03425274,0.0008041041,0.000008390949,0.9642536,0.0002035195],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002163992,0.0001798512,0.1021583,0.00001824025,0.002536984,0.0007754233,0.00005457239,0.000234342,0.8940207],"genre_scores_gemma":[0.0006990782,0.000320298,0.005886792,0.000007351274,0.0006805436,0.00008905725,0.0005569369,0.0004943581,0.9912656],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2088557,"threshold_uncertainty_score":0.6147891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005239891968949983,"score_gpt":0.1847017508861985,"score_spread":0.1794618589172485,"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."}}