{"id":"W4238248834","doi":"10.32920/ryerson.14661999","title":"Natural zeolite removal capacity of heavy metallic ions","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Sorption; Sorbent; Clinoptilolite; Zeolite; Wastewater; Effluent; Industrial wastewater treatment; Adsorption; Pollutant; Environmental science; Ion exchange; Waste management; Chemistry; Environmental engineering; Engineering; Catalysis","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003572293,0.0002090182,0.0004334243,0.00004342431,0.00006684434,0.00005672781,0.0003742546,0.000154895,0.001258175],"category_scores_gemma":[0.00004743621,0.0001749772,0.0004178327,0.0001968804,0.0001901268,0.00007894488,0.00116606,0.0004685596,0.00007486993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000133513,"about_ca_system_score_gemma":0.00001660436,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01429928,"about_ca_topic_score_gemma":0.0001452228,"domain_scores_codex":[0.9982345,0.0001700679,0.0003784649,0.0005109881,0.0004708005,0.0002352071],"domain_scores_gemma":[0.9990209,0.00003550284,0.0001442177,0.00068173,0.00001945885,0.0000981624],"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":[0.00004663434,0.001349099,0.04363386,0.000822674,0.002232299,0.0001979491,0.008818491,0.01525645,0.9152638,0.001581735,0.003334113,0.007462869],"study_design_scores_gemma":[0.0004132335,0.00004526091,0.06644359,0.0003356978,0.0008717194,0.00005664134,0.001132755,0.003961714,0.9112351,0.006286805,0.007546646,0.001670816],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950791,0.0001460269,0.0002187817,0.000348465,0.0004856301,0.00006873885,0.00001536369,0.00004959829,0.00358828],"genre_scores_gemma":[0.9794633,0.00002869364,0.0118585,0.00003885199,0.00009084719,0.000005755351,0.00004763631,0.00001115263,0.008455287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02280973,"threshold_uncertainty_score":0.9996548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03759366118349697,"score_gpt":0.2632442182902366,"score_spread":0.2256505571067396,"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."}}