{"id":"W2966403254","doi":"10.11159/icnfa19.113","title":"Bioremediation of Silver and Recovery of AgNPs for the Fabrication of AgNPs Functionalized Antibacterial Polycaprolactone Membrane","year":2019,"lang":"en","type":"article","venue":"Proceedings of the World Congress on New Technologies","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Polycaprolactone; Silver nanoparticle; Bioremediation; Chemistry; Fabrication; Membrane; Materials science; Nanotechnology; Nuclear chemistry; Nanoparticle; Organic chemistry; Bacteria; Polymer; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001473037,0.0001127787,0.0002479064,0.0002135892,0.00002932615,0.00001366385,0.0002570263,0.00009237712,0.00002471436],"category_scores_gemma":[0.0003709002,0.00007493874,0.00006893193,0.0003971246,0.0001372455,0.0002294025,0.00004153065,0.00009585993,6.117784e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001494404,"about_ca_system_score_gemma":0.00002168585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009306184,"about_ca_topic_score_gemma":0.000007819196,"domain_scores_codex":[0.9992284,0.000002481245,0.0003673454,0.0001242326,0.0001881473,0.00008945075],"domain_scores_gemma":[0.9988981,0.0002286116,0.0004619319,0.0001362834,0.0002654971,0.000009565822],"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":[0.000425692,0.00003548023,0.002360087,0.00058218,0.0000958283,5.067006e-9,0.00006339864,0.0002802793,0.9766665,0.005449628,0.002277704,0.01176323],"study_design_scores_gemma":[0.0006248629,0.00009798125,0.003047049,0.0001343409,0.0000452513,5.960879e-7,0.0002869415,0.0008758919,0.9884228,0.001665194,0.004720836,0.00007823674],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948119,0.0006969448,0.00008573989,0.001221399,0.0008654653,0.0007061851,0.0000253783,0.0001789482,0.001408036],"genre_scores_gemma":[0.9974639,0.000589054,0.0004180416,0.000009898426,0.00002395681,0.00002426914,0.00000276368,0.00001249887,0.001455639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01175633,"threshold_uncertainty_score":0.3055913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0112332128454944,"score_gpt":0.2268636817754861,"score_spread":0.2156304689299917,"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."}}