{"id":"W2511285872","doi":"10.1149/ma2016-02/22/1654","title":"Synthesis of Novel Graphene Composite Adsorbent for Water Treatment By Adsorption and Electrochemical Regeneration","year":2016,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Adsorption; Graphene; Regeneration (biology); Composite number; Electrochemistry; Materials science; Water treatment; Chemical engineering; Nanotechnology; Chemistry; Composite material; Electrode; Environmental science; Environmental engineering; Organic chemistry; Engineering; Cell biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001607508,0.0001053121,0.0001194798,0.00002512206,0.00004435714,0.00001104796,0.00006524525,0.00007360781,0.00002811231],"category_scores_gemma":[0.00009033604,0.00006371308,0.00003247539,0.00003171104,0.00008212164,0.0001185268,0.00002550819,0.00002114758,0.00001216422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008386746,"about_ca_system_score_gemma":0.000002598273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004934664,"about_ca_topic_score_gemma":0.00001100219,"domain_scores_codex":[0.9992375,0.00001216706,0.0002254613,0.0002273432,0.0001220694,0.0001754576],"domain_scores_gemma":[0.9995886,0.0001361991,0.0001015212,0.0001274134,0.000009653171,0.00003662407],"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":[0.00003184612,0.00008587095,0.0004168724,0.000006280726,0.000008463894,7.039326e-8,0.000035531,0.0005030881,0.9968093,0.000006230188,0.000154929,0.001941531],"study_design_scores_gemma":[0.0003789597,0.00009995665,0.0008362066,0.00002530315,0.00001715479,0.000002381177,0.000007104358,0.0002872054,0.9974422,0.0001341776,0.0006779397,0.00009137368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974316,0.00002822244,0.0005628599,0.0007603608,0.00002214472,0.0002061647,0.0000127143,0.00005551065,0.0009204012],"genre_scores_gemma":[0.9962109,0.0000554433,0.003495978,0.00001432993,0.00001672754,0.00005889041,0.00001295848,0.000009484609,0.0001252976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002933118,"threshold_uncertainty_score":0.2598144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310187941570629,"score_gpt":0.2277947606474015,"score_spread":0.2146928812316952,"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."}}