{"id":"W4291805246","doi":"10.21203/rs.3.rs-1898174/v1","title":"Arsenic removal performance of granular adsorbents using novel clinoptilolites modified with iron nanoparticles","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adsorption; Chitosan; Bead; Nuclear chemistry; Arsenic; Sodium alginate; Freundlich equation; Chemistry; Clinoptilolite; Sodium hydroxide; Chromatography; Materials science; Sodium; Zeolite; Organic chemistry; Catalysis; Composite material","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":[0.0001453486,0.0003925038,0.0003105569,0.0003672087,0.0001748922,0.0003637029,0.000224453,0.0003725633,0.0002428838],"category_scores_gemma":[0.0001339195,0.0001718193,0.0004147696,0.0001812881,0.0001502142,0.0001915933,0.000195293,0.0002415778,0.0001514519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003431279,"about_ca_system_score_gemma":0.0002311152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002747118,"about_ca_topic_score_gemma":0.00671704,"domain_scores_codex":[0.9998647,0.00001446245,0.00001327959,0.00002354244,0.00005489014,0.00002911143],"domain_scores_gemma":[0.9999318,0.00000760516,0.00001669999,0.000004656004,0.00002517046,0.0000140934],"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":[0.00004823543,0.00002024218,0.0003361129,0.00008210712,0.00001089569,0.00004163312,0.000006716235,0.0001777064,0.9980433,0.00001450528,0.00002211962,0.001196451],"study_design_scores_gemma":[0.0000150802,0.0002355475,0.004593008,0.000007794652,0.00002665169,0.000100989,0.00002835627,0.002194623,0.9918384,0.00001158708,0.0009357164,0.00001228028],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966733,0.001045497,0.001588917,0.00004119747,0.00001711315,0.000018802,0.00008603601,0.00003846814,0.0004906696],"genre_scores_gemma":[0.995537,0.0005227821,0.002795042,0.00003157918,0.000005019553,0.00001324925,0.00009695406,0.000008025079,0.000990322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002747118,"threshold_uncertainty_score":0.005462229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07271436712930515,"score_gpt":0.3477333093021016,"score_spread":0.2750189421727964,"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."}}