{"id":"W4408005324","doi":"10.3389/fenvc.2025.1511440","title":"Characterization of the fate of primary and re-precipitated silver nanoparticles in lake water model systems","year":2025,"lang":"en","type":"article","venue":"Frontiers in Environmental Chemistry","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Primary (astronomy); Characterization (materials science); Nanoparticle; Environmental science; Environmental chemistry; Nanotechnology; Chemistry; Materials science; Physics","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":[0.0001284881,0.0002875611,0.0002637252,0.0002221779,0.0002106722,0.00028858,0.0002507491,0.0002853574,0.0003527015],"category_scores_gemma":[0.000149605,0.0001149746,0.0002351815,0.0001704816,0.0001723558,0.0001856611,0.0002632376,0.0002924019,0.0001179702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004267687,"about_ca_system_score_gemma":0.0002801645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007913137,"about_ca_topic_score_gemma":0.008753693,"domain_scores_codex":[0.9998693,0.00001288857,0.000008499042,0.00004280947,0.00004529907,0.00002123842],"domain_scores_gemma":[0.9999446,0.000008407918,0.00001620159,0.00000321912,0.00002142018,0.000006135112],"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":[0.00005505349,0.00001845152,0.001219718,0.00004986296,0.000007074797,0.00004022444,0.00005424107,0.000422216,0.9969157,0.00001867797,0.00002534426,0.00117343],"study_design_scores_gemma":[0.00001379393,0.0007231826,0.01451547,0.00000844136,0.00003261004,0.0000701863,0.000143144,0.008368002,0.9746338,0.00006609497,0.001407743,0.00001740154],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980546,0.0001211105,0.001181382,0.00001508049,0.000002537071,0.00002573523,0.0002532352,0.00003018231,0.0003160951],"genre_scores_gemma":[0.9939078,0.0002733531,0.003639795,0.00003210915,0.000003047501,0.00007989982,0.0005716888,0.00001800324,0.001474332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007913137,"threshold_uncertainty_score":0.01573414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004947303666930634,"score_gpt":0.1742368629948484,"score_spread":0.1692895593279178,"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."}}