{"id":"W2971822601","doi":"10.3390/nano9091258","title":"Morphological Transformation of Silver Nanoparticles from Commercial Products: Modeling from Product Incorporation, Weathering through Use Scenarios, and Leaching into Wastewater","year":2019,"lang":"en","type":"article","venue":"Nanomaterials","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Carleton University","funders":"Environment and Climate Change Canada","keywords":"Leaching (pedology); Nanomaterials; X-ray photoelectron spectroscopy; Weathering; Materials science; Wastewater; Nanoparticle; Silver nanoparticle; Environmental chemistry; Energy-dispersive X-ray spectroscopy; Chemical engineering; Inductively coupled plasma mass spectrometry; Nanotoxicology; Weathering steel; Raw material; Metallurgy; Nanotechnology; Chemistry; Scanning electron microscope; Mass spectrometry; Environmental science; Composite material; Environmental engineering; Corrosion; Chromatography; Geology; Organic chemistry; Soil science; Engineering","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":[0.0002709499,0.0003990813,0.0003108665,0.0003365172,0.0002128697,0.0005280438,0.0003941741,0.0007048458,0.0007768184],"category_scores_gemma":[0.0004489227,0.0002564657,0.0006855655,0.0003714556,0.0002166372,0.0004368967,0.0002351616,0.0004695361,0.0002337517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008148102,"about_ca_system_score_gemma":0.000395717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123103,"about_ca_topic_score_gemma":0.01021363,"domain_scores_codex":[0.9998831,0.00001271788,0.000009337375,0.00003103412,0.00004059933,0.00002323014],"domain_scores_gemma":[0.9998098,0.00009762691,0.00002958006,0.00001108477,0.00004343855,0.000008510408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008433469,0.0007024112,0.02764683,0.0009086929,0.0001175598,0.0007176565,0.0003945915,0.5732485,0.37492,0.001157987,0.0006711774,0.01867129],"study_design_scores_gemma":[0.00004268707,0.0006839318,0.01502959,0.00001726678,0.00005896532,0.0001541084,0.0001919754,0.8317379,0.1497585,0.0004584391,0.00182833,0.0000382643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953158,0.0002321559,0.002229427,0.00002836035,0.000005371279,0.00004321044,0.0005603007,0.00003401727,0.001551347],"genre_scores_gemma":[0.9952366,0.0005107632,0.002707505,0.00001330242,0.000001955897,0.00006177937,0.0003755757,0.0000186287,0.001073956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0123103,"threshold_uncertainty_score":0.0244773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03588047123938871,"score_gpt":0.247034987122188,"score_spread":0.2111545158827993,"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."}}