{"id":"W2776528350","doi":"10.1115/1.4038853","title":"Numerical Modeling of Heavy-Oil Recovery Using Electromagnetic Radiation/Hydraulic Fracturing Considering Thermal Expansion Effect","year":2017,"lang":"en","type":"article","venue":"Journal of Heat Transfer","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Petroleum engineering; Adiabatic process; Thermal; Mechanics; Dielectric heating; Volumetric flow rate; Materials science; Environmental science; Nuclear engineering; Thermodynamics; Engineering; Physics","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":[0.0004540688,0.0002396633,0.0006420251,0.0002444467,0.0002368439,0.00009393756,0.0002841485,0.0001447661,0.00005235447],"category_scores_gemma":[0.00007405566,0.0001954,0.0004328191,0.0000786256,0.00003974015,0.0004983693,0.00001225613,0.0005374944,0.000002274965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001095294,"about_ca_system_score_gemma":0.000059403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001553117,"about_ca_topic_score_gemma":0.000004201091,"domain_scores_codex":[0.9983323,0.00008691438,0.0007013869,0.0001453411,0.0003890895,0.0003449424],"domain_scores_gemma":[0.999254,0.000130748,0.00004836557,0.0003408269,0.00007655416,0.0001494383],"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":[0.0001034623,0.00002197418,0.0002482892,0.0001623895,0.0002002977,0.00004142845,0.0001791258,0.8541432,0.139749,2.575514e-7,0.000005661968,0.00514488],"study_design_scores_gemma":[0.0008548868,0.000233651,0.0006872069,0.0003388125,0.0002099641,0.0001265379,0.00001392725,0.7524145,0.2448675,0.00001368437,0.00004281099,0.0001964718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.936887,0.002303755,0.05986629,0.0001238998,0.0003248817,0.00004616806,0.000001208603,0.00003052648,0.000416247],"genre_scores_gemma":[0.9982356,0.000629176,0.0007577094,0.00002328783,0.0002960248,0.000001455109,7.852365e-7,0.00005041201,0.000005531006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1051185,"threshold_uncertainty_score":0.7968179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0116658856132478,"score_gpt":0.234851526320507,"score_spread":0.2231856407072592,"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."}}