{"id":"W2776974546","doi":"10.1016/j.chemosphere.2017.12.049","title":"LuminoTox as a tool to optimize ozone doses for the removal of contaminants and their associated toxicity","year":2017,"lang":"en","type":"article","venue":"Chemosphere","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ozone; Toxicity; Effluent; Chemistry; Wastewater; Environmental chemistry; Contamination; Acute toxicity; Sewage treatment; Environmental science; Environmental engineering; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004925792,0.0004600306,0.0002936132,0.0003151498,0.0001993057,0.0007620495,0.0003810564,0.0003625334,0.0009916674],"category_scores_gemma":[0.0004658368,0.0002538757,0.0003335785,0.0002530468,0.0001850153,0.0004137979,0.0005407943,0.000588119,0.0002847532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004000649,"about_ca_system_score_gemma":0.0004833968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005625447,"about_ca_topic_score_gemma":0.001237719,"domain_scores_codex":[0.999639,0.00006289935,0.0000235817,0.00006433627,0.0001763889,0.00003371268],"domain_scores_gemma":[0.9998139,0.00005726234,0.00005932564,0.00002039276,0.00003331725,0.00001579668],"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":[0.00006956684,0.0000308327,0.0004176519,0.00004683468,0.00000915173,0.00001369387,0.00001523747,0.0006018422,0.993244,0.0001805533,0.00009227992,0.005278347],"study_design_scores_gemma":[0.000006313156,0.0001680107,0.0007044306,0.000004623167,0.00001875295,0.00003146537,0.00001292154,0.002039822,0.9955514,0.00005046171,0.00140552,0.0000062354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8829792,0.003560414,0.1062104,0.0004266604,0.00009434935,0.0001119264,0.0008219762,0.001042312,0.00475291],"genre_scores_gemma":[0.9236441,0.003311818,0.06526358,0.000194668,0.00001749684,0.0001068814,0.0007530974,0.0002584196,0.006449846],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0009916674,"threshold_uncertainty_score":0.003317475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03191628894313885,"score_gpt":0.3009744198357275,"score_spread":0.2690581308925886,"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."}}