{"id":"W1133886329","doi":"10.1128/9781555818098.ch14","title":"Biosorption Processes for Heavy Metal Removal","year":2014,"lang":"en","type":"book-chapter","venue":"ASM Press eBooks","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Biosorption; Biomass (ecology); Metal; Chemistry; Ion exchange; Heavy metals; Metal ions in aqueous solution; Environmental engineering; Waste management; Environmental chemistry; Environmental science; Adsorption; Engineering; Ion; Sorption; Ecology; Biology; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002163915,0.001252738,0.0007297494,0.00101919,0.0006559504,0.001442365,0.001054187,0.001341605,0.02613401],"category_scores_gemma":[0.0001912571,0.0004307147,0.0008523129,0.001610996,0.0005290463,0.001854424,0.001029489,0.002251813,0.02558144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007809786,"about_ca_system_score_gemma":0.000420125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005818335,"about_ca_topic_score_gemma":0.001223393,"domain_scores_codex":[0.9996523,0.00002245294,0.00001296174,0.00007998765,0.0002098823,0.00002241839],"domain_scores_gemma":[0.9999437,0.00001751564,0.000005154659,0.000007574704,0.00002124986,0.000004816722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005918165,0.0002760481,0.0001406644,0.005034993,0.00005446353,0.0003825829,0.0006736068,0.003302212,0.1288594,0.13176,0.1263284,0.6031284],"study_design_scores_gemma":[0.000005287763,0.00003423265,0.0001628669,0.0002170483,0.0000119215,0.0004152702,0.00004402548,0.001152297,0.01568663,0.01181079,0.9704419,0.00001758506],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005713042,0.4005665,0.1627577,0.002758255,0.005105582,0.000397201,0.000808561,0.001896213,0.419997],"genre_scores_gemma":[0.02261493,0.1684297,0.06714363,0.002484291,0.0007320339,0.0002854901,0.0009164366,0.0005645173,0.736829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02613401,"threshold_uncertainty_score":0.08742696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03222346259202622,"score_gpt":0.2400859523369623,"score_spread":0.2078624897449361,"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."}}