{"id":"W3212191017","doi":"10.1021/acsomega.1c05169","title":"Applied Artificial Neural Network for Hydrogen Sulfide Solubility in Natural Gas Purification","year":2021,"lang":"en","type":"article","venue":"ACS Omega","topic":"Industrial Gas Emission Control","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Chulalongkorn University","keywords":"Solubility; Hydrogen sulfide; Artificial neural network; Ionic liquid; Amine gas treating; Mean squared error; Chemistry; Materials science; Biological system; Computer science; Organic chemistry; Mathematics; Artificial intelligence","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":[0.0006522586,0.0006043942,0.0005441752,0.0005352206,0.000261506,0.0007466691,0.0006359378,0.0008143193,0.002149604],"category_scores_gemma":[0.0009866148,0.0002755341,0.0005597363,0.0004678917,0.0001731125,0.0005099985,0.0003356102,0.0008262104,0.0003851609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007331078,"about_ca_system_score_gemma":0.0007497826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009460236,"about_ca_topic_score_gemma":0.00696652,"domain_scores_codex":[0.9998279,0.000034864,0.00001712835,0.00004355794,0.00004319326,0.00003338951],"domain_scores_gemma":[0.9997575,0.000101567,0.00001709009,0.000007531533,0.0001071359,0.000009221036],"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":[0.0003533423,0.0002400054,0.00308544,0.0002858237,0.0001611234,0.0001285058,0.00005223965,0.6129358,0.007157158,0.00302118,0.004285629,0.3682939],"study_design_scores_gemma":[0.000003679922,0.00002381695,0.0001983978,0.00000593215,0.000008442146,0.000004721252,0.000004133054,0.9983782,0.0008479886,0.0002531942,0.000268161,0.00000330637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2000688,0.01398504,0.7633404,0.001631902,0.001024545,0.0001725198,0.0004555323,0.002348066,0.01697333],"genre_scores_gemma":[0.9332014,0.002335472,0.05295484,0.0002244251,0.0001191365,0.0001337489,0.0003944149,0.00004434876,0.01059225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009460236,"threshold_uncertainty_score":0.01881033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02132230457960097,"score_gpt":0.2348417784928842,"score_spread":0.2135194739132832,"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."}}