{"id":"W1964850653","doi":"10.1002/clen.201000027","title":"Removal of Brilliant Green Dye from Aqueous Solutions Using Home Made Activated Carbons","year":2010,"lang":"en","type":"article","venue":"CLEAN - Soil Air Water","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Partenariat Canadien Contre Le Cancer; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Activated carbon; Adsorption; Brilliant green; Aqueous solution; Enthalpy; Chemistry; Chromatography; Effluent; Chemical engineering; Nuclear chemistry; Volume (thermodynamics); Porosity; Materials science; Organic chemistry; Environmental engineering; Environmental science; Thermodynamics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001333538,0.0001987522,0.0002143088,0.00005775766,0.0001863691,0.00001835308,0.0002552072,0.0001816288,0.004900623],"category_scores_gemma":[0.000009115226,0.0001471912,0.0001455747,0.0001476246,0.0004486684,0.0001968926,0.0002663912,0.0002871979,0.0009133773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001094264,"about_ca_system_score_gemma":0.00001653057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006590934,"about_ca_topic_score_gemma":0.001508954,"domain_scores_codex":[0.9985073,0.00004779575,0.0003147876,0.000358938,0.0003158939,0.000455314],"domain_scores_gemma":[0.9992782,0.00001374905,0.00009643283,0.0003865012,0.00001301007,0.0002120575],"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":[0.00003481335,0.00007468481,0.001502799,0.0000034727,0.00002028935,0.00004458839,0.0002623765,0.0002161778,0.9932112,0.00002007225,0.0002422111,0.004367337],"study_design_scores_gemma":[0.001445148,0.0001282184,0.09654928,0.00003944,0.0001204275,0.0008310193,0.0003270046,0.01666212,0.83737,0.003060477,0.04245193,0.001014947],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955944,0.00000745721,0.0000891001,0.0005874591,0.0004085688,0.0001207653,0.00009762344,0.00009818748,0.002996433],"genre_scores_gemma":[0.9946724,0.000005675269,0.001017657,0.0002243302,0.0001517245,0.000001474541,0.00004084584,0.00002939538,0.003856567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1558412,"threshold_uncertainty_score":0.9998645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669193495127032,"score_gpt":0.2181236397268477,"score_spread":0.2014317047755774,"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."}}