{"id":"W2312507689","doi":"10.1021/ef400286m","title":"Thermodynamic Modeling and Process Simulation through PIONA Characterization","year":2013,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Process Optimization and Integration","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Virtual Materials Group (Canada)","funders":"Virtual Materials Group","keywords":"Characterization (materials science); Component (thermodynamics); Raw material; Process engineering; Refinery; Distillation; Constant (computer programming); Biological system; Process (computing); Chemical process; Chemistry; Computer science; Materials science; Thermodynamics; Organic chemistry; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001906144,0.0001026656,0.00007908981,0.00004287625,0.0000535779,0.00006655194,0.00004599578,0.00006623455,0.0001201296],"category_scores_gemma":[0.000009805006,0.00009641487,0.0000133459,0.00010913,0.000008839213,0.0009032628,0.000006413219,0.00004536038,0.00001172337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002102395,"about_ca_system_score_gemma":0.000006990348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001683612,"about_ca_topic_score_gemma":0.000003307691,"domain_scores_codex":[0.9995391,0.000008386364,0.0001478979,0.0001167916,0.00008389418,0.0001039723],"domain_scores_gemma":[0.9997718,0.000009183482,0.00002420894,0.00007340734,0.00009373759,0.00002768797],"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":[0.000001535384,0.000006719554,0.0000176758,0.00002325175,0.000007567733,6.563594e-8,0.0003380942,0.9281484,0.05872869,0.002114727,0.000004349745,0.01060893],"study_design_scores_gemma":[0.00009452748,0.000006833252,0.0001453088,0.00001615359,0.000003725839,4.884209e-7,0.00003169338,0.990858,0.005256055,0.003326661,0.0001476785,0.0001128325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4158401,0.00006836076,0.5813317,0.00003092026,0.00005876568,0.00004812855,0.000001424464,0.0001655601,0.002455002],"genre_scores_gemma":[0.9987473,0.0001998222,0.0005023588,0.0001303043,0.00005809369,0.000048791,0.0001491216,0.00002602793,0.000138131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5829073,"threshold_uncertainty_score":0.3931684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00924886816124623,"score_gpt":0.2177485575464735,"score_spread":0.2084996893852273,"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."}}