{"id":"W2117019099","doi":"10.5185/amlett.2011.4256","title":"Biosynthesis of silver nanoparticles using murraya koenigii (curry leaf): An investigation on the effect of broth concentration in reduction mechanism and particle size","year":2011,"lang":"en","type":"article","venue":"Advanced Materials Letters","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":224,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ministry of Agriculture, Food and Rural Affairs; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph","keywords":"Silver nanoparticle; Murraya; Nanocrystalline material; Materials science; Particle size; Transmission electron microscopy; Nanoparticle; Reducing agent; Particle (ecology); Spectrophotometry; Nuclear chemistry; Crystal violet; Chemical engineering; Analytical Chemistry (journal); Scanning electron microscope; Nanotechnology; Chromatography; Chemistry; Composite material; Botany","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":[0.0006887739,0.0001377838,0.0002475305,0.00002805133,0.00008506783,0.00002743196,0.0001192198,0.00004079638,0.000103791],"category_scores_gemma":[0.0001313147,0.0001021792,0.00002436277,0.000144095,0.0002085018,0.0003887564,0.00002428886,0.00002976156,0.000005118899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002812953,"about_ca_system_score_gemma":0.00001110194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001621187,"about_ca_topic_score_gemma":0.000006323943,"domain_scores_codex":[0.9985554,0.0003848683,0.0004358076,0.0002644403,0.0001544577,0.0002050426],"domain_scores_gemma":[0.9991179,0.0002333526,0.0002916678,0.0002822891,0.00002667892,0.00004809652],"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":[0.0002015207,0.0000419637,0.0004481776,0.00003498664,0.000003885132,3.968477e-7,0.0007071733,0.000105513,0.9956551,0.002530878,0.000001668113,0.0002687349],"study_design_scores_gemma":[0.0003442694,0.0001905753,0.002181801,0.000093438,0.00002669068,0.000001695509,0.0001405229,0.0001065368,0.9955481,0.001259512,7.672973e-7,0.0001061185],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990103,0.00001353987,0.0000500206,0.0002449393,0.0001325579,0.0005010563,0.00001767388,0.00002665106,0.00000324137],"genre_scores_gemma":[0.9977086,0.000008655819,0.002082853,0.00008612458,0.00002353457,0.00007281765,0.000001245703,0.00001550541,7.003996e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002032833,"threshold_uncertainty_score":0.4166745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02715027665577895,"score_gpt":0.2370116453132183,"score_spread":0.2098613686574393,"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."}}