{"id":"W2768817960","doi":"10.1166/jnn.2018.14698","title":"Adsorption of Cu<sup>2+</sup> Ions from Aqueous Solutions on Nano-Titanate Engelhard Titanosilicate-2 (ETS-2)","year":2017,"lang":"en","type":"article","venue":"Journal of Nanoscience and Nanotechnology","topic":"Chemical Synthesis and Characterization","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Sorbent; Aqueous solution; Adsorption; Materials science; X-ray photoelectron spectroscopy; Thermogravimetric analysis; Titanate; Metal ions in aqueous solution; Ion exchange; Nuclear chemistry; Inorganic chemistry; Metal; Ion; Chemical engineering; Physical chemistry; Chemistry; Organic chemistry; Ceramic; Composite material","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":[0.0002699667,0.0001241078,0.000266262,0.0001028502,0.000357458,0.00004385112,0.0006345813,0.0002148002,0.0002191765],"category_scores_gemma":[0.0004611727,0.00009741409,0.00008576872,0.0001486431,0.0007717813,0.0003873123,0.0002232217,0.0002090044,0.00003732911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008989069,"about_ca_system_score_gemma":0.00002355589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001248361,"about_ca_topic_score_gemma":0.00002149623,"domain_scores_codex":[0.9987765,0.00003030351,0.0003870231,0.0002470464,0.0003146776,0.0002444462],"domain_scores_gemma":[0.9988015,0.00007922448,0.000625556,0.0003698298,0.00003467355,0.00008924646],"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":[0.0000310506,0.0001131044,0.005330453,0.000002063653,0.000007309649,0.000004550876,0.00008270767,0.00004285833,0.9728312,0.0002620254,0.0002000496,0.02109259],"study_design_scores_gemma":[0.0006847551,0.0006749546,0.06330427,0.000147771,0.00006642838,0.0000855293,0.0001689043,0.002119577,0.9162072,0.007313091,0.008933992,0.0002935209],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962987,0.0001020804,0.0003568869,0.002631759,0.0001294926,0.00007454675,0.00002131155,0.00001384297,0.0003713911],"genre_scores_gemma":[0.9985554,0.000735922,0.0005015524,0.00008959236,0.00003803687,0.00000276667,0.000001349083,0.000006730961,0.00006865276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05797381,"threshold_uncertainty_score":0.3972431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01674781971227271,"score_gpt":0.2324426137277374,"score_spread":0.2156947940154647,"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."}}