{"id":"W1906285468","doi":"10.1144/petgeo2013-039","title":"Estimating barrier shale extent and optimizing well placement in heavy oil reservoirs","year":2015,"lang":"en","type":"article","venue":"Petroleum Geoscience","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cenovus Energy (Canada); Canadian Natural Resources; University of Alberta","funders":"","keywords":"Geology; Environmental geology; Geobiology; Oil shale; Igneous petrology; Economic geology; Metamorphic petrology; Telmatology; Regional geology; Hydrogeology; Petroleum engineering; Gemology; Palaeogeography; Engineering geology; Unconventional oil; Petrology; Mining engineering; Seismology; Volcanism; Geotechnical engineering; Paleontology; Tectonics","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":[0.0006526038,0.0001437346,0.000181906,0.0002303927,0.00008619449,0.0001096159,0.0002109177,0.00004356279,0.00003533518],"category_scores_gemma":[0.00009824087,0.0001339777,0.00003211103,0.000419714,0.00007587932,0.0003438166,0.00009821052,0.0001611511,0.0000364953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000124299,"about_ca_system_score_gemma":0.00003975321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001493951,"about_ca_topic_score_gemma":0.0001731387,"domain_scores_codex":[0.9986566,0.00003626967,0.0002694107,0.0002842082,0.0003882058,0.0003652983],"domain_scores_gemma":[0.9994159,0.00002717505,0.0000312036,0.0002270894,0.00003123657,0.0002673918],"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":[0.000006037583,0.00001455423,0.001601654,0.00002348537,0.000004639552,0.0000111703,0.0008709386,0.995874,0.0008905358,0.0000178116,0.0001438836,0.000541318],"study_design_scores_gemma":[0.0003478121,0.00002641749,0.0002108801,0.00004034796,0.000005726555,0.000005190794,0.001040365,0.9965295,0.0004010645,0.00003938171,0.001190157,0.0001631381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416789,0.0007195739,0.04151469,0.0004182935,0.0003838653,0.00004733585,0.000003456993,0.0001722296,0.01506159],"genre_scores_gemma":[0.9844306,0.00007257502,0.01391315,0.00006615127,0.00004897906,0.00002858434,0.000003535251,0.00001581671,0.001420686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04275156,"threshold_uncertainty_score":0.5463451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924829619603048,"score_gpt":0.2409600591809541,"score_spread":0.2217117629849236,"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."}}