{"id":"W2088839951","doi":"10.1016/j.watres.2012.08.016","title":"QSAR-like models: A potential tool for the selection of PhACs and EDCs for monitoring purposes in drinking water treatment systems – A review","year":2012,"lang":"en","type":"review","venue":"Water Research","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Public Health Agency of Canada","keywords":"Quantitative structure–activity relationship; Biochemical engineering; Human health; TRACE (psycholinguistics); Process (computing); Environmental chemistry; Environmental science; Chemistry; Risk analysis (engineering); Computer science; Machine learning; Environmental health; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001239632,0.00198402,0.003110729,0.00188184,0.0002013544,0.001390097,0.00163938,0.001120485,0.002576428],"category_scores_gemma":[0.001282926,0.0005727772,0.001791791,0.003084584,0.0003488797,0.001430947,0.0005905964,0.001430415,0.001244862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005465971,"about_ca_system_score_gemma":0.001143995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001870419,"about_ca_topic_score_gemma":0.002557306,"domain_scores_codex":[0.999648,0.00007019209,0.00003872976,0.0000637124,0.0001595745,0.00001982587],"domain_scores_gemma":[0.9992647,0.0004210593,0.0001171501,0.00002624029,0.0001547054,0.00001617574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009740316,0.0002185127,0.0007066481,0.02746115,0.0006043221,0.0001808002,0.00004424713,0.03020263,0.01230231,0.008312088,0.01363857,0.9062314],"study_design_scores_gemma":[0.0001467801,0.001184072,0.002812604,0.007023893,0.002570014,0.001273688,0.0002108319,0.05715611,0.02825278,0.01693759,0.8821026,0.0003290644],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002144417,0.9645962,0.02883361,0.0006259449,0.0003025712,0.00008909899,0.0007368646,0.0002154715,0.00245584],"genre_scores_gemma":[0.00831652,0.978775,0.01112031,0.0002232789,0.000143426,0.00006047783,0.0005051515,0.00001731084,0.0008384841],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003110729,"threshold_uncertainty_score":0.00861907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2706278815364281,"score_gpt":0.4333310561862824,"score_spread":0.1627031746498542,"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."}}