{"id":"W4323655315","doi":"10.2118/212755-ms","title":"Life Cycle Analysis (LCA) and Carbon Intensity of In-Situ Reflux (ISR) Process Using Renewable Solvents","year":2023,"lang":"en","type":"article","venue":"","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Greenhouse gas; Renewable energy; Environmental science; Process engineering; Waste management; Propane; Life-cycle assessment; Electricity generation; Petroleum engineering; Engineering; Chemistry; Power (physics); Electrical engineering; Production (economics); Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006768142,0.0006439445,0.0006495784,0.001435229,0.0005037846,0.0007777379,0.0004443196,0.0005718084,0.002701753],"category_scores_gemma":[0.0005079437,0.0002247174,0.001422654,0.001655346,0.0002792253,0.0007147987,0.0002675244,0.0006961832,0.0005333206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001139016,"about_ca_system_score_gemma":0.0004245158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004853284,"about_ca_topic_score_gemma":0.005577568,"domain_scores_codex":[0.9994605,0.00005651363,0.00004105056,0.0001033754,0.0002684843,0.00007007139],"domain_scores_gemma":[0.9994487,0.0001407715,0.00009663826,0.0000411135,0.0002524077,0.00002034182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001984657,0.0008432344,0.03192037,0.001755944,0.0003681021,0.0005935626,0.0002530387,0.07469036,0.8170128,0.001828443,0.001435091,0.06731451],"study_design_scores_gemma":[0.00002617098,0.001890135,0.02569173,0.00008070475,0.0001601266,0.0001473469,0.0002382789,0.07084681,0.89616,0.0007050954,0.003973156,0.00008040774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859672,0.002083159,0.004387395,0.000072622,0.00003336818,0.000086306,0.003659545,0.0001183763,0.003592042],"genre_scores_gemma":[0.9932585,0.001016604,0.001902693,0.00002045697,0.000004104576,0.00009774135,0.001276355,0.00002739252,0.002396168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004853284,"threshold_uncertainty_score":0.009650052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02905153755497629,"score_gpt":0.3168794501606417,"score_spread":0.2878279126056654,"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."}}