{"id":"W3197690555","doi":"10.21203/rs.3.rs-836957/v1","title":"Process Optimization and Adsorptive Mechanism for Reactive Blue 19 Dye by Magnetic Crosslinked Chitosan/MgO/Fe3O4 Biocomposite","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Universiti Teknologi MARA","keywords":"Adsorption; Biocomposite; Potentiometric titration; Box–Behnken design; Chitosan; Glutaraldehyde; Fourier transform infrared spectroscopy; Materials science; Freundlich equation; Response surface methodology; Nuclear chemistry; Titration; Chemical engineering; Chemistry; Analytical Chemistry (journal); Chromatography; Composite material; Composite number; Inorganic chemistry; Electrode; Physical chemistry; 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":[0.0002012529,0.0003856928,0.0002841032,0.0002686419,0.0001303379,0.0001957835,0.0002425261,0.0002469784,0.0006797898],"category_scores_gemma":[0.0001658168,0.0001444584,0.0004059559,0.0002081124,0.0001645305,0.0001892478,0.0001608386,0.0002520237,0.00021012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002958002,"about_ca_system_score_gemma":0.0001752469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001185715,"about_ca_topic_score_gemma":0.002154405,"domain_scores_codex":[0.9998749,0.00001777966,0.00001224989,0.00002291806,0.00004687315,0.00002526274],"domain_scores_gemma":[0.9999453,0.000009014159,0.00001954172,0.000004558509,0.00001453994,0.000007096859],"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":[0.00003028358,0.00001898084,0.00004701255,0.00005303825,0.000003119018,0.00002296229,0.000006112772,0.0001153962,0.9988702,0.00002227722,0.0000116556,0.0007990384],"study_design_scores_gemma":[0.000005903744,0.0001114608,0.0007129684,0.000002581618,0.00001129573,0.00002520181,0.000007380088,0.0009865018,0.9976785,0.00001066886,0.0004438386,0.000003715633],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892731,0.001248698,0.008062696,0.00008485701,0.00003101033,0.00007145172,0.0001213077,0.00009597217,0.001010741],"genre_scores_gemma":[0.9902455,0.0007917604,0.006982229,0.00003449609,0.000009176111,0.00004671845,0.0001152156,0.00001810594,0.001756725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001185715,"threshold_uncertainty_score":0.002357602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02662597789537162,"score_gpt":0.3411722434256179,"score_spread":0.3145462655302462,"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."}}