{"id":"W4409787654","doi":"10.61091/jcmcc127a-303","title":"Efficient numerical simulation and method optimization for pressure distribution calculation in petroleum seepage field","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer simulation; Distribution (mathematics); Petroleum engineering; Field (mathematics); Petroleum; Geology; Computer science; Mathematics; Simulation; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006816871,0.0007139957,0.001035318,0.0005960464,0.0007753537,0.0008801881,0.001050758,0.0009400169,0.003187979],"category_scores_gemma":[0.001323884,0.0005177339,0.0008206532,0.0007759687,0.0005615721,0.0008736511,0.0008662331,0.0007932456,0.0005459389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007091934,"about_ca_system_score_gemma":0.001777116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01188833,"about_ca_topic_score_gemma":0.005856664,"domain_scores_codex":[0.9996529,0.00009121632,0.00002294839,0.00005125592,0.0001375864,0.00004400236],"domain_scores_gemma":[0.9995273,0.0002223462,0.00004470273,0.00003691506,0.0001456649,0.00002304771],"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":[0.00002345142,0.00002732811,0.0005255594,0.00008768328,0.00001358515,0.00005518577,0.0000378975,0.9713694,0.001734812,0.006049607,0.0006156738,0.01945986],"study_design_scores_gemma":[0.000003564874,0.00000325043,0.00002438513,0.000002140237,0.000001202875,0.000004006861,0.000003349039,0.9990814,0.0001528012,0.0004222653,0.0003002884,0.000001492066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01449469,0.00025641,0.9793643,0.0001153357,0.00004636816,0.00006217978,0.00008238771,0.0004160157,0.005162247],"genre_scores_gemma":[0.4499148,0.0007846672,0.541867,0.00009607453,0.00005280057,0.0007407146,0.000402302,0.0003451441,0.005796529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01188833,"threshold_uncertainty_score":0.02363825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009678930476153027,"score_gpt":0.2947005082437,"score_spread":0.285021577767547,"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."}}