{"id":"W3114896176","doi":"10.3390/pr9010078","title":"Green Synthesis of Copper Oxide Nanoparticles Using Protein Fractions from an Aqueous Extract of Brown Algae Macrocystis pyrifera","year":2020,"lang":"en","type":"article","venue":"Processes","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Comisión Nacional de Investigación Científica y Tecnológica","keywords":"Fourier transform infrared spectroscopy; Dynamic light scattering; Nanoparticle; Zeta potential; Materials science; Aqueous solution; Copper; Size-exclusion chromatography; Chemical engineering; Nuclear chemistry; Chemistry; Nanotechnology; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00007683914,0.0004272867,0.0002318026,0.0002085468,0.0001695195,0.0002095569,0.0001289625,0.000166997,0.000187234],"category_scores_gemma":[0.00007883013,0.0001157179,0.0002076596,0.0001367374,0.0001180789,0.0001536535,0.0002464351,0.0002037659,0.000109464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002475447,"about_ca_system_score_gemma":0.0001708588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009597387,"about_ca_topic_score_gemma":0.001507046,"domain_scores_codex":[0.9999262,0.000006828036,0.000005253206,0.00002313678,0.00002815089,0.00001039593],"domain_scores_gemma":[0.9999611,0.000004785789,0.00001306383,0.000004071093,0.000009346176,0.000007590296],"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":[0.000006547095,0.000003924903,0.00004396151,0.00002402461,0.000001557584,0.00001869501,0.000006320977,0.00002430461,0.9992117,0.00001241969,0.000006778605,0.0006398201],"study_design_scores_gemma":[0.000001720992,0.00007599789,0.001197495,0.000002589803,0.000006527109,0.0000548373,0.0000111548,0.0004171104,0.9972746,0.00001490423,0.0009410361,0.000002150558],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861274,0.001596048,0.01035126,0.00005818411,0.00003142235,0.00004108548,0.0002263249,0.0001427761,0.001425583],"genre_scores_gemma":[0.9826558,0.001335943,0.0120893,0.00003832028,0.00001028112,0.0000321504,0.0003925906,0.00003877702,0.00340685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009597387,"threshold_uncertainty_score":0.001908362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0370253389793026,"score_gpt":0.277137939336017,"score_spread":0.2401126003567144,"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."}}