{"id":"W4416115037","doi":"10.1139/facets-2025-0110","title":"Whole-lake silver nanoparticle addition promotes phosphorus and silver excretion by yellow perch ( <i>Perca flavescens</i> )","year":2025,"lang":"en","type":"article","venue":"FACETS","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Excretion; Perch; Nutrient; Silver nanoparticle; Phosphorus; Aquatic animal; Ecotoxicology; Aquatic ecosystem","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002723935,0.0001712706,0.0001916393,0.00004084537,0.0002972,0.0001673179,0.0001583133,0.00009494532,0.0008445127],"category_scores_gemma":[0.00005861933,0.0001569397,0.00004482513,0.0002520447,0.000162486,0.0002616144,0.0000815637,0.00008283886,0.0006908756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003730498,"about_ca_system_score_gemma":0.00003623672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002870433,"about_ca_topic_score_gemma":0.00003561323,"domain_scores_codex":[0.9986472,0.00007417499,0.0002705817,0.0004514636,0.000209046,0.0003475796],"domain_scores_gemma":[0.9993501,0.00008349238,0.00006259979,0.0003278895,0.0000699321,0.0001059315],"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":[0.00001695354,0.0001293822,0.0005074217,0.00001768996,0.000005051476,7.128839e-7,0.0001757626,0.000004218636,0.9562894,0.0002915301,0.04022739,0.002334481],"study_design_scores_gemma":[0.0003340678,0.00003896628,0.003963699,0.00005950742,0.00002987849,0.000002379679,0.0001217252,0.0004170941,0.9262721,0.0005995338,0.06798717,0.0001738778],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995652,0.0004597622,0.0001778775,0.002039659,0.0001324862,0.0004125468,0.0002671967,0.0001364155,0.0007220091],"genre_scores_gemma":[0.996352,0.00005960391,0.000536972,0.0003640344,0.00003261938,0.000149544,0.00005042311,0.00001589861,0.002438959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0300173,"threshold_uncertainty_score":0.9246822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008424181291816633,"score_gpt":0.2334106030302872,"score_spread":0.2249864217384705,"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."}}