{"id":"W2937267300","doi":"10.1680/jwama.17.00059","title":"Development of a solar electrocoagulation technology for decentralised water treatment","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Institution of Civil Engineers - Water Management","topic":"Advanced oxidation water treatment","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université Laval","funders":"","keywords":"Electrocoagulation; Turbidity; Environmental science; Photovoltaic system; Charge controller; Materials science; Environmental engineering; Ultraviolet; Intensity (physics); Current (fluid); Current density; Radiant intensity; Power (physics); Radiation; Optoelectronics; Electrical engineering; Battery (electricity); Optics; Physics; Engineering","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":[0.0001475319,0.0001790431,0.0002250295,0.0001462041,0.00006380195,0.000006255253,0.0002610223,0.00005684327,0.0000975344],"category_scores_gemma":[0.000003452242,0.0001006672,0.00008867059,0.0001608209,0.00009698455,0.0002801439,0.0001666383,0.00003199459,0.00002076451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004225428,"about_ca_system_score_gemma":0.000006567925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000446209,"about_ca_topic_score_gemma":0.000005631755,"domain_scores_codex":[0.9987473,0.000002418088,0.0004377662,0.0002463122,0.0002805478,0.0002856704],"domain_scores_gemma":[0.9996201,0.000003576006,0.0001482189,0.0001519771,0.00004814674,0.00002796958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001226772,0.0002950632,0.003735667,0.0003255473,0.0002284652,1.372502e-7,0.001932155,0.02903574,0.9563968,0.00481528,0.00003748155,0.003075012],"study_design_scores_gemma":[0.001153141,0.0001221435,0.0009684323,0.00005342315,0.00007042156,9.218811e-7,0.0001563728,0.0005803399,0.9819798,0.001000132,0.01379371,0.0001211186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879335,0.000007967698,0.008099925,0.0003015456,0.000110023,0.001625705,0.000003151675,0.00003785375,0.00188033],"genre_scores_gemma":[0.9789127,0.000008763961,0.02031228,0.00001082138,0.000004790411,0.0001604676,0.00001439895,0.0000128341,0.0005630095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0284554,"threshold_uncertainty_score":0.410509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005972659191508165,"score_gpt":0.1959752021981047,"score_spread":0.1900025430065965,"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."}}