{"id":"W4316194046","doi":"10.1002/jctb.7318","title":"Impact of low levels of silver, zinc and copper nanoparticles on bacterial removal and potential synergy in water treatment applications","year":2023,"lang":"en","type":"article","venue":"Journal of Chemical Technology & Biotechnology","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Carleton University","keywords":"Zinc; BLISS; Chemistry; Copper; Water treatment; Metal; Nanoparticle; Nuclear chemistry; Environmental chemistry; Environmental engineering; Nanotechnology; Materials science; Environmental science; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002059862,0.0001518288,0.0004971853,0.0005095441,0.00003444633,0.000008948648,0.0002511774,0.0004337528,0.0000366852],"category_scores_gemma":[0.0000720296,0.0001012887,0.00008489623,0.000434854,0.0008121593,0.00007143855,0.0001417787,0.0001533287,0.000008701959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006538777,"about_ca_system_score_gemma":0.0000384092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001067561,"about_ca_topic_score_gemma":0.000001433419,"domain_scores_codex":[0.9986882,0.00002756374,0.0006318764,0.0002383161,0.0001198249,0.0002942405],"domain_scores_gemma":[0.999254,0.00007637258,0.0002720768,0.0002707385,0.00007207556,0.00005475142],"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":[0.0001207016,0.0002792391,0.0002682404,0.00001291007,0.00003097209,0.00001468007,0.00002329815,0.0000128137,0.9844056,0.001945205,0.0000145348,0.01287182],"study_design_scores_gemma":[0.0008383808,0.0005515805,0.0008472329,0.00004167734,0.00003149143,0.0001984123,0.00004961315,0.00003110907,0.9929394,0.004240337,0.0001410652,0.00008969498],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968376,0.0001262012,0.00002399383,0.002726281,0.00003030575,0.0001625582,0.00003257856,0.00005598172,0.000004528461],"genre_scores_gemma":[0.9987467,0.0002258043,0.0009534248,0.00000657288,0.00002439752,0.0000252253,0.000001433389,0.00001202774,0.000004448273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01278212,"threshold_uncertainty_score":0.4130434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01217474819713592,"score_gpt":0.2645113016564518,"score_spread":0.2523365534593159,"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."}}