{"id":"W2094891685","doi":"10.2118/2007-027","title":"A Unified Model for Prediction of CSOR in Steam-Based Bitumen Recovery","year":2007,"lang":"en","type":"article","venue":"Canadian International Petroleum Conference","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laricina Energy (Canada)","funders":"","keywords":"Computer science","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":[0.0007412798,0.000826803,0.001328095,0.0009032169,0.000609736,0.00145806,0.001885388,0.002091226,0.003757589],"category_scores_gemma":[0.001744109,0.0007814636,0.001134546,0.0005974134,0.0008663372,0.001164026,0.0007709295,0.0009271075,0.0006710018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001952553,"about_ca_system_score_gemma":0.001743099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03001138,"about_ca_topic_score_gemma":0.01200909,"domain_scores_codex":[0.9996998,0.00006708063,0.00001374669,0.00007142992,0.00007863932,0.00006934762],"domain_scores_gemma":[0.9994557,0.0002610536,0.00006969291,0.00002102851,0.0001597444,0.0000326485],"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":[0.000008662552,0.000009526863,0.0001687627,0.000009429621,0.000006185636,0.00002330162,0.000012184,0.9968567,0.000438142,0.001456428,0.00008433162,0.000926361],"study_design_scores_gemma":[0.000001777773,0.000003852721,0.00003523938,0.000001054192,0.000001751974,0.000001357135,0.000001689367,0.9995854,0.00004895173,0.0002467967,0.00007047248,0.000001611947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1733547,0.0005069145,0.803107,0.0006197799,0.0001058668,0.0001813272,0.0008171106,0.001382475,0.01992481],"genre_scores_gemma":[0.9642943,0.0003013202,0.02033709,0.00007341114,0.00003896442,0.0003245205,0.0003199239,0.0001291343,0.01418135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03001138,"threshold_uncertainty_score":0.05967343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03154986033695475,"score_gpt":0.2468882739033542,"score_spread":0.2153384135663994,"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."}}