{"id":"W3204888166","doi":"10.1021/acsami.1c13920","title":"Efficient Gold Recovery from Cyanide Solution Using Magnetic Activated Carbon","year":2021,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Queen's University","keywords":"Activated carbon; Adsorption; Materials science; Cyanide; Carbon fibers; Chemical engineering; Desorption; Specific surface area; Magnetism; Inorganic chemistry; Nanotechnology; Catalysis; Organic chemistry; Composite material; Metallurgy; Chemistry","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":[0.000201977,0.0007168869,0.0005229715,0.0007292479,0.000355645,0.0003402575,0.000526841,0.0009736852,0.000868897],"category_scores_gemma":[0.0002814367,0.0002533797,0.0004819852,0.0004369238,0.0002502882,0.000430248,0.0004553304,0.0004997763,0.0004787794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004847527,"about_ca_system_score_gemma":0.0003398295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001906733,"about_ca_topic_score_gemma":0.004404117,"domain_scores_codex":[0.9996495,0.0000278458,0.00002342728,0.00008636999,0.0001542661,0.00005849288],"domain_scores_gemma":[0.9998946,0.00001765282,0.0000171925,0.00001313191,0.00004518174,0.00001227722],"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":[0.0000334028,0.00001432166,0.00005241904,0.00009166775,0.000005455718,0.00007622547,0.00001278739,0.0001778862,0.9963071,0.00007018149,0.0001083384,0.003050265],"study_design_scores_gemma":[0.000007168886,0.00006408348,0.0003149953,0.0000061058,0.000006312634,0.00005338365,0.00001022709,0.002174855,0.9961965,0.00002358044,0.001132363,0.00001043623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9648231,0.004340387,0.02193687,0.0003686328,0.0001780222,0.0001436181,0.0003781224,0.0007322663,0.007098865],"genre_scores_gemma":[0.9714101,0.00177235,0.02132274,0.0001298086,0.00002883309,0.00006466901,0.0002881329,0.00007211818,0.00491129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001906733,"threshold_uncertainty_score":0.003791332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146516521043351,"score_gpt":0.2164380869563439,"score_spread":0.2017864348520088,"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."}}