{"id":"W2470304971","doi":"10.1139/cjc-2016-0113","title":"Synthesis and characterization of a novel chloromethylated polystyrene-g-2-adenine chelating resin and its application to preconcentrate and detect the concentration of mercury ions in edible mushroom samples","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemistry; Chelating resin; Adsorption; Polystyrene; Langmuir adsorption model; Fourier transform infrared spectroscopy; Mercury (programming language); Chelation; Nuclear chemistry; Metal ions in aqueous solution; Thermogravimetric analysis; Langmuir; Metal; Inorganic chemistry; Organic chemistry; Chemical engineering; Polymer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001802982,0.0004069025,0.000203628,0.0003201764,0.0001520614,0.00017479,0.0002273334,0.0002821855,0.0008214735],"category_scores_gemma":[0.0001908692,0.000128134,0.0002888046,0.0002175749,0.0001507694,0.0001666318,0.0001339728,0.0003154922,0.0004710951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001307801,"about_ca_system_score_gemma":0.0002566301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006722071,"about_ca_topic_score_gemma":0.001412192,"domain_scores_codex":[0.99985,0.00001691914,0.0000144844,0.00003650209,0.00006437858,0.00001763981],"domain_scores_gemma":[0.999824,0.00002274167,0.00004445467,0.00002382848,0.00004824183,0.00003669345],"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":[0.00001648571,0.00001250326,0.00006920023,0.00004822264,0.000002549832,0.00003326206,0.000008908552,0.00007560587,0.997656,0.00002319348,0.00001550161,0.002038587],"study_design_scores_gemma":[0.000004326516,0.0002652842,0.002299557,0.000003420624,0.00001434729,0.000176714,0.00001612824,0.0005814981,0.9942205,0.00001224128,0.002398116,0.000007860832],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519622,0.002224019,0.04206381,0.0001347574,0.00004081083,0.000183416,0.0007506744,0.0003038369,0.002336507],"genre_scores_gemma":[0.9440332,0.001269303,0.04778605,0.00008909246,0.0000256908,0.00009510398,0.001140914,0.00005263889,0.005508203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008214735,"threshold_uncertainty_score":0.002748072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136033185948091,"score_gpt":0.2047922101906959,"score_spread":0.193431878331215,"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."}}