{"id":"W2300882514","doi":"10.1021/acssuschemeng.5b01612","title":"Development of a Green Technology for Mercury Recycling from Spent Compact Fluorescent Lamps Using Iron Oxides Nanoparticles and Electrochemistry","year":2016,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Mercury (programming language); Electrolysis; Nanoparticle; Electrochemistry; Chemistry; Environmental chemistry; Materials science; Nanotechnology; Electrode","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":[0.00009223574,0.0002006546,0.0002251095,0.0000593458,0.00006984436,0.00002285148,0.0001170082,0.0001328352,0.0000180824],"category_scores_gemma":[0.00009848894,0.0001896031,0.00002989986,0.0001561014,0.00002963733,0.0002012124,0.00003474687,0.00009746022,5.679411e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002302484,"about_ca_system_score_gemma":0.00006316575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006573906,"about_ca_topic_score_gemma":6.034304e-7,"domain_scores_codex":[0.998951,0.000001958581,0.0003424344,0.0002143262,0.0001027432,0.000387603],"domain_scores_gemma":[0.9995173,0.00007272585,0.00006350855,0.0001564642,0.0001082163,0.00008179943],"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":[0.00001382308,0.00001552529,0.0001244524,0.0009056237,0.00004669893,0.00000331393,0.000142742,0.003887757,0.9938667,0.00009855902,0.0000159394,0.0008788953],"study_design_scores_gemma":[0.0003440989,0.000005417172,0.00004599397,0.0001433521,0.00002128602,0.000009731009,0.0007697842,0.004691596,0.9874413,0.0001082161,0.006187601,0.0002316065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861164,0.001048536,0.01230872,0.00008669842,0.00002455196,0.0001219035,0.000005589318,0.0002263254,0.00006125456],"genre_scores_gemma":[0.9908811,0.00007753989,0.00866158,0.000003075984,0.00004930857,0.00002298427,0.000009387768,0.00003844651,0.0002565891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006425352,"threshold_uncertainty_score":0.7731789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009190292233815667,"score_gpt":0.2242395443211792,"score_spread":0.2150492520873635,"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."}}