{"id":"W3086642131","doi":"10.2118/199028-pa","title":"Optimization of Recovery by Huff ‘n’ Puff Gas Injection in Shale-Oil Reservoirs Using the Climbing-Swarm Derivative-Free Algorithm","year":2020,"lang":"en","type":"article","venue":"SPE Reservoir Evaluation & Engineering","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Petroleum engineering; Oil shale; Shale gas; Algorithm; Particle swarm optimization; Engineering; Environmental science; Computer science; Waste management","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":[0.0005908351,0.0006424258,0.0005221604,0.0003367621,0.0002567786,0.0004709792,0.000632835,0.0009781655,0.001413064],"category_scores_gemma":[0.001201831,0.0002943515,0.00046123,0.0002314374,0.0003899773,0.0002854964,0.0003888742,0.0004091141,0.0001782331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005732591,"about_ca_system_score_gemma":0.001080898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0128835,"about_ca_topic_score_gemma":0.007537629,"domain_scores_codex":[0.9998788,0.00003220089,0.000006425699,0.00002198152,0.00003052536,0.00003004932],"domain_scores_gemma":[0.9995385,0.0003042302,0.00004578821,0.00001781074,0.00006597781,0.00002769098],"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":[0.00003229811,0.00002138471,0.0003778779,0.00002925769,0.00001136041,0.00003784359,0.00001330225,0.992254,0.001020778,0.0004108934,0.0001884237,0.005602525],"study_design_scores_gemma":[0.000004142133,0.00001328642,0.00007711947,0.000001736459,0.000001642309,0.000002071848,0.000003572639,0.9995214,0.0002272854,0.00007432976,0.00007200633,0.000001355802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3785638,0.0004402636,0.6061427,0.0004577345,0.00005453788,0.0002320286,0.0001551688,0.0009208948,0.01303296],"genre_scores_gemma":[0.909259,0.00008039133,0.08795761,0.00005838568,0.000006396724,0.0001289171,0.00008936762,0.0000432804,0.002376556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0128835,"threshold_uncertainty_score":0.02561706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04854355401270358,"score_gpt":0.2954124570832737,"score_spread":0.2468689030705701,"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."}}