{"id":"W4400695893","doi":"10.2139/ssrn.4895857","title":"Polyethylene Glycol Diglycidyl Ether- Chitosan/Algae/ Montmorillonite Clay Composite for Toxic Cationic Dye Removal: Statistical Modelling and Desirability Functions","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Montmorillonite; Polyethylene glycol; Diglycidyl ether; Chitosan; Cationic polymerization; Composite number; Bentonite; Chemistry; Pulp and paper industry; Algae; Chemical engineering; Ether; Nuclear chemistry; Materials science; Polymer chemistry; Organic chemistry; Composite material; Botany; Epoxy; Bisphenol A; Biology","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":[0.001085356,0.000431833,0.0003191342,0.0004166438,0.000161938,0.0003495142,0.0003384369,0.0004857747,0.0005877903],"category_scores_gemma":[0.00166932,0.0001896704,0.0006995128,0.0003537459,0.0001834722,0.0003422569,0.000277599,0.0003850849,0.0001639767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006486684,"about_ca_system_score_gemma":0.0003556754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00637547,"about_ca_topic_score_gemma":0.004320319,"domain_scores_codex":[0.9998237,0.00005767164,0.00001035345,0.00003770789,0.00004674697,0.00002386088],"domain_scores_gemma":[0.9990708,0.0006495877,0.0001095171,0.00003633051,0.0001084338,0.00002539689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001367113,0.000267513,0.004922343,0.0003759351,0.0001265674,0.000186085,0.0001165372,0.6389955,0.3137726,0.002898133,0.0004410519,0.03653058],"study_design_scores_gemma":[0.000006323608,0.0001480646,0.001045129,0.000002533549,0.00002669977,0.00001981277,0.000009463918,0.9348316,0.06352643,0.0002395895,0.0001319327,0.00001250472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8156866,0.000363186,0.1820356,0.0001246221,0.00001969525,0.00004886048,0.0001661172,0.0003405523,0.001214816],"genre_scores_gemma":[0.9879072,0.0001527746,0.009900174,0.00001761955,0.000005037612,0.00002503845,0.00008659895,0.00003458302,0.001870874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00637547,"threshold_uncertainty_score":0.01267672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02289179819091593,"score_gpt":0.2750890890756392,"score_spread":0.2521972908847233,"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."}}