{"id":"W4400093401","doi":"10.1021/acs.iecr.4c01190","title":"Process for the Remediation of Titanogypsum (Red Gypsum) Using Weak Acid and CaCl<sub>2</sub> to Produce Saleable α-Gypsum and FeCl<sub>2</sub>·4H<sub>2</sub>O","year":2024,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Gypsum; Environmental remediation; Process (computing); Chemistry; Mineralogy; Nuclear chemistry; Inorganic chemistry; Waste management; Metallurgy; Materials science; Contamination; Computer science; Engineering","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":[0.00008081074,0.0002960988,0.0002527201,0.0001480218,0.0001854539,0.0002000682,0.0002223638,0.0003846742,0.0005445562],"category_scores_gemma":[0.00008458183,0.0001549398,0.0002326307,0.000118981,0.0003088962,0.0002164729,0.0002980264,0.0003902534,0.0002410279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002917845,"about_ca_system_score_gemma":0.0003512503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001367326,"about_ca_topic_score_gemma":0.002110153,"domain_scores_codex":[0.9999475,0.000004123278,0.000002651408,0.00001191588,0.00002603359,0.000007857405],"domain_scores_gemma":[0.9999696,0.000004366541,0.0000110554,0.000004547782,0.000005700564,0.000004685289],"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":[0.00001764147,0.00000931425,0.000105941,0.00004314001,0.000004688621,0.0000402994,0.00001342588,0.0002404161,0.9981633,0.00005656551,0.00003834904,0.001267142],"study_design_scores_gemma":[0.00001330907,0.0001117991,0.001493015,0.000002754866,0.0000162427,0.0001235865,0.00002508857,0.002305396,0.9936474,0.00005443912,0.002201935,0.000005183208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9657201,0.001705303,0.02971559,0.0003092866,0.00007666046,0.0001003735,0.0001461624,0.0002538923,0.001972592],"genre_scores_gemma":[0.9781293,0.0007481542,0.0178393,0.00007532548,0.000008288343,0.00003272162,0.00009701877,0.00001907085,0.003050858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001367326,"threshold_uncertainty_score":0.002718747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07872483576878958,"score_gpt":0.3206496519889203,"score_spread":0.2419248162201307,"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."}}