{"id":"W2749467713","doi":"10.3390/polym9090394","title":"CO2-Responsive Graft Modified Chitosan for Heavy Metal (Nickel) Recovery","year":2017,"lang":"en","type":"article","venue":"Polymers","topic":"Membrane Separation and Gas Transport","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chitosan; Adsorption; Glycidyl methacrylate; Wastewater; Methacrylate; Polymer; Grafting; Materials science; Monomer; Chemical engineering; Polymerization; Tertiary amine; Amine gas treating; Polymer chemistry; Chemistry; Organic chemistry; Waste management; Composite material","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":[0.00007551625,0.0001539436,0.0002005263,0.0000669257,0.000214388,0.00006220732,0.0002211856,0.00007595025,0.0001072573],"category_scores_gemma":[0.00003456451,0.0001572852,0.0001481782,0.0000292162,0.00005366941,0.0002126047,0.000008593176,0.00008429159,0.00003141871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001092088,"about_ca_system_score_gemma":0.00002708387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005003381,"about_ca_topic_score_gemma":0.0000573986,"domain_scores_codex":[0.9992619,0.00001042809,0.000183018,0.000170607,0.0001121065,0.0002619397],"domain_scores_gemma":[0.9993626,0.00004497838,0.00004510515,0.0004214522,0.00001215362,0.0001137438],"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":[0.002736162,0.0002147269,0.0007739439,0.0006513674,0.001775529,0.00007496667,0.002423262,0.05152686,0.8302342,0.01183738,0.01556392,0.08218767],"study_design_scores_gemma":[0.002595628,0.0001632176,0.005841429,0.00003973764,0.0001599265,0.00001411674,0.0001156111,0.01760846,0.9406475,0.0003030702,0.03174323,0.0007680226],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9246176,0.0007927222,0.008168773,0.001025523,0.002887417,0.0006419517,0.0002230052,0.0004177705,0.06122528],"genre_scores_gemma":[0.9973719,0.00007189029,0.0002808469,0.0001556104,0.0001373439,0.00004698972,0.0000521813,0.00003783209,0.00184545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1104133,"threshold_uncertainty_score":0.6413903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0233524970485139,"score_gpt":0.263747750166866,"score_spread":0.2403952531183521,"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."}}