{"id":"W2002222590","doi":"10.2118/0813-0058-jpt","title":"Finding Pathways to Produce Heavy Oil From Canadian Carbonates","year":2013,"lang":"en","type":"article","venue":"Journal of Petroleum Technology","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Asphalt; Oil sands; Synthetic crude; Engineering; Petroleum; Petroleum industry; Steam-assisted gravity drainage; Crude oil; Fossil fuel; Petroleum engineering; Mining engineering; Geology; Archaeology; Waste management; Unconventional oil; Environmental engineering; Geography; Paleontology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002086555,0.0001387947,0.0002934257,0.001014923,0.00003868849,0.00003866991,0.0003287875,0.0001849907,0.00008478906],"category_scores_gemma":[0.0002628584,0.0001298936,0.00005879981,0.0003577265,0.00001635112,0.0001225078,0.00002285036,0.0004491881,0.00005781189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000210079,"about_ca_system_score_gemma":0.00006382576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001881021,"about_ca_topic_score_gemma":0.0008665773,"domain_scores_codex":[0.9990284,0.00001756738,0.0003678073,0.0001098507,0.0001418223,0.0003345846],"domain_scores_gemma":[0.9992932,0.00006153723,0.00005641242,0.0002377305,0.0001167701,0.000234316],"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":[0.000004067454,0.000008372313,0.003234388,0.00001962403,0.00007398595,0.00004272396,0.0001811806,0.9151807,0.05685097,0.0001818783,0.002044325,0.02217782],"study_design_scores_gemma":[0.002504297,0.0007015425,0.02685437,0.0005305611,0.00009639258,0.0003608381,0.001435823,0.6103351,0.1601535,0.009853646,0.1855531,0.00162095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990966,0.0007497026,0.004607643,0.002018085,0.0006459794,0.00002945822,0.000005783304,0.0001697932,0.0008075088],"genre_scores_gemma":[0.9670438,0.0000389865,0.03254073,0.00003668547,0.0001902385,0.000006047047,0.0000010892,0.00003203791,0.0001104567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3048457,"threshold_uncertainty_score":0.5296909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145835221518517,"score_gpt":0.2261706083618155,"score_spread":0.2147122561466303,"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."}}