{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001383828,0.0004511192,0.0005518868,0.000216215,0.0001709986,0.0003353871,0.0002421052,0.0003419179,0.0003210966],"category_scores_gemma":[0.0001736496,0.0001842808,0.0003333347,0.0001793039,0.00013143,0.000252507,0.0002510503,0.0005629795,0.000170176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002266342,"about_ca_system_score_gemma":0.0001737733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000759848,"about_ca_topic_score_gemma":0.001638365,"domain_scores_codex":[0.9999088,0.00001328088,0.00001084026,0.000021148,0.00003198153,0.0000140184],"domain_scores_gemma":[0.9998827,0.00002838485,0.00003661933,0.00001022241,0.0000233564,0.00001869949],"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":[0.00001287908,0.000007908295,0.00002850865,0.00003279626,0.000001463719,0.00001460805,0.000007615916,0.00001037871,0.9995695,0.000006346391,0.000003733741,0.0003044158],"study_design_scores_gemma":[0.000002778239,0.0001672274,0.001322539,0.000004148805,0.00001603003,0.0000613798,0.00001354157,0.0001318495,0.9975677,0.000009454759,0.0006993164,0.000003939902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942845,0.001823108,0.002400074,0.0001220644,0.00002063661,0.00004425143,0.0001656857,0.00005581068,0.001083914],"genre_scores_gemma":[0.9855547,0.001469082,0.009377418,0.0000807285,0.000009917522,0.00005707173,0.0004401928,0.00004467001,0.002966275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000759848,"threshold_uncertainty_score":0.001644313,"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."}}