{"id":"W2090770631","doi":"10.1007/s11053-006-9017-2","title":"Optimization of SAGD Well Elevation","year":2006,"lang":"en","type":"article","venue":"Natural Resources Research","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Elevation (ballistics); Oil sands; Asphalt; Steam-assisted gravity drainage; Petroleum engineering; Mineral resource classification; Geology; Environmental science; Mining engineering; Engineering; Geography; Geochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007464361,0.00008394763,0.0001148159,0.0003449799,0.00005893377,0.00003837784,0.0001738237,0.00009750737,0.00009521238],"category_scores_gemma":[0.0001884381,0.00007775764,0.00004063924,0.0007167946,0.00004439022,0.0001043646,0.00002693891,0.0003647056,0.00001641099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006518264,"about_ca_system_score_gemma":0.000007912198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000590094,"about_ca_topic_score_gemma":0.00000447963,"domain_scores_codex":[0.9987055,0.0001044903,0.000226035,0.0001188518,0.0005837195,0.0002613753],"domain_scores_gemma":[0.9992107,0.0003157744,0.00001813785,0.000189472,0.0002285298,0.00003745599],"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":[0.00001144492,0.000006598893,0.000403409,0.00006628642,0.000004393807,7.623154e-7,0.00004775502,0.989672,0.00724866,0.0001999524,0.001088937,0.001249795],"study_design_scores_gemma":[0.0002227305,0.00001705884,0.003085619,0.00002005776,0.00000163103,7.137303e-7,0.00002303567,0.9759241,0.007629366,0.0001415177,0.01285401,0.00008010719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414425,0.001666114,0.03530659,0.00004937917,0.0001449284,0.0001635878,0.000002763633,0.0002070827,0.02101698],"genre_scores_gemma":[0.9800364,0.00004991778,0.01796617,0.00000159989,0.0001556414,0.000007063033,0.0000229574,0.00002474735,0.001735446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03859389,"threshold_uncertainty_score":0.3170865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695103442254555,"score_gpt":0.3301072327462016,"score_spread":0.303156198323656,"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."}}