{"id":"W7161544449","doi":"10.1016/j.engfor.2026.03.014","title":"Unlocking insights - leveraging large language models for enhanced knowledge management in natural gas E&amp;P industry (WGC2025 Regional Gas Award)","year":2025,"lang":"en","type":"article","venue":"Energy Foresight","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"","keywords":"Knowledge base; Natural gas; Knowledge-based systems; Gas industry; Work (physics); Natural language","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002248966,0.0002809801,0.000291827,0.0005752344,0.0001047251,0.00005151211,0.0002732966,0.0002499858,0.00001323145],"category_scores_gemma":[0.00002837677,0.0002832044,0.0001207133,0.0005707071,0.00001545535,0.0002124622,0.00008185348,0.0003915919,0.000002515439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002308965,"about_ca_system_score_gemma":0.0000306301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001623829,"about_ca_topic_score_gemma":0.0001464307,"domain_scores_codex":[0.9986088,0.00005785911,0.0003612784,0.0003305542,0.0001642861,0.0004772675],"domain_scores_gemma":[0.9992933,0.0002143876,0.00003086478,0.0003450419,0.0000471072,0.00006928029],"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":[0.00002399199,0.00002782904,0.0000173277,0.0001703268,0.0001052201,0.000007722611,0.0008305261,0.942775,0.001021039,0.04800357,0.002004178,0.005013267],"study_design_scores_gemma":[0.001498932,0.000006272832,0.0001016375,0.0002817277,0.00002096394,8.746425e-7,0.0001734083,0.9012304,0.01039263,0.008004755,0.07795425,0.0003341403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1600984,0.004996315,0.8121727,0.00006770271,0.0008333807,0.0001995194,0.000004359324,0.000354569,0.02127311],"genre_scores_gemma":[0.9747543,0.0001559635,0.01519135,0.00007009829,0.0001546118,0.000153696,0.00008416594,0.00005214448,0.009383673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8146559,"threshold_uncertainty_score":0.999962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941293354195359,"score_gpt":0.287310637306,"score_spread":0.2678977037640464,"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."}}