{"id":"W4253628438","doi":"10.32920/ryerson.14657550","title":"Investigation Of Hybrid SAGD Using Carbon Dioxide, Propane, Nitrogen and Methane","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Methane; Propane; Carbon dioxide; Petroleum engineering; Chemistry; Nitrogen; Permeability (electromagnetism); Isothermal process; Porosity; Solvent; Environmental science; Chemical engineering; Thermodynamics; Organic chemistry; 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":[0.0002583532,0.0002082656,0.0004001372,0.0002554515,0.0001678967,0.0003699651,0.0002293818,0.0002252123,0.0003072588],"category_scores_gemma":[0.0002845312,0.0001187489,0.0002692023,0.0002848635,0.0003055405,0.0004135922,0.00045547,0.0001784768,0.00008035223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002653719,"about_ca_system_score_gemma":0.0001809201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007575427,"about_ca_topic_score_gemma":0.0008524192,"domain_scores_codex":[0.9998117,0.00002998711,0.00001209872,0.00003241421,0.00008442936,0.00002937255],"domain_scores_gemma":[0.9999003,0.00003438461,0.00002161407,0.000008699947,0.0000236352,0.00001133102],"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":[0.0001921438,0.00005902653,0.001119011,0.0001677244,0.00001264422,0.0001189462,0.00004237997,0.002910622,0.9878489,0.0002222435,0.00002362833,0.007282794],"study_design_scores_gemma":[0.00001361426,0.0006209184,0.001587022,0.000005020665,0.00001378131,0.0000819483,0.00006333845,0.02209534,0.9744205,0.00006560754,0.001024776,0.000008000711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941372,0.0003283308,0.005035219,0.00002182001,0.000006527682,0.00001305022,0.00003751026,0.00004339734,0.000377008],"genre_scores_gemma":[0.9958435,0.0002205968,0.003580307,0.000008116615,0.000002001709,0.00001013671,0.00003628779,0.000006528318,0.0002924591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007575427,"threshold_uncertainty_score":0.001925409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02286771236753798,"score_gpt":0.2349660100937793,"score_spread":0.2120982977262413,"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."}}