{"id":"W1973824175","doi":"10.1016/j.camwa.2009.08.042","title":"Multirange multi-relaxation time Shan–Chen model with extended equilibrium","year":2009,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Lattice Boltzmann Simulation Studies","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Chen; Mathematics; Relaxation (psychology); Collision; Prandtl number; Work (physics); Stability (learning theory); Term (time); Statistical physics; Flow (mathematics); Operator (biology); Function (biology); Distribution function; Applied mathematics; Mechanics; Thermodynamics; Physics; Computer science; Chemistry; Geometry","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":[0.00008092492,0.0002841246,0.0002969124,0.0001127302,0.0001183312,0.00007394781,0.0002480215,0.00006937896,0.000007103608],"category_scores_gemma":[0.000005746338,0.0002313257,0.00004391609,0.0003295361,0.00006278491,0.0002302396,0.00003373115,0.0001340327,0.0001615536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007907319,"about_ca_system_score_gemma":0.00002221719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.257172e-7,"about_ca_topic_score_gemma":0.000002037239,"domain_scores_codex":[0.998849,0.000008182343,0.000328807,0.0002775465,0.0002568205,0.0002796308],"domain_scores_gemma":[0.9989541,0.0001051357,0.0001179079,0.0005623457,0.0001547483,0.0001057444],"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":[0.00001103905,0.0003076829,0.00003153224,0.0001282247,0.0001394007,0.000001648704,0.002424505,0.9840229,0.001841649,0.004125033,0.0007267762,0.006239609],"study_design_scores_gemma":[0.0008085639,0.00004573682,0.0006178179,0.00006829302,0.00008179442,0.000009103893,0.00005121366,0.9959372,0.0001981165,0.001599225,0.0002643741,0.0003185918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01312141,0.00009453147,0.9823861,0.0001725587,0.00001382804,0.001056034,0.00001383961,0.0009538874,0.002187883],"genre_scores_gemma":[0.4017002,0.000007183625,0.5974531,0.00008637245,0.0000482818,0.000235221,0.00003877516,0.00005777344,0.000373102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3885788,"threshold_uncertainty_score":0.943319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005669152655808,"score_gpt":0.2445792728935433,"score_spread":0.2245225813669852,"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."}}