{"id":"W4237937909","doi":"10.2523/59748-ms","title":"Production Optimization of Gas Wells by Automated Unloading: Case Histories","year":2000,"lang":"en","type":"article","venue":"","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kensington Health","funders":"Dominion Energy","keywords":"Automation; Production (economics); Natural gas field; Work (physics); Field (mathematics); Computer science; Scale (ratio); Petroleum engineering; Systems engineering; Environmental science; Engineering; Natural gas; Mechanical engineering","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":[0.0001149197,0.0000862982,0.0001059982,0.00006033074,0.00002772975,0.0000104634,0.00003709905,0.00005390458,0.0006512544],"category_scores_gemma":[0.00002956291,0.00008705648,0.00002274868,0.0002139174,0.00001284599,0.000131539,0.000002401386,0.00004934227,0.000007946071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004917508,"about_ca_system_score_gemma":0.000004037569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000266582,"about_ca_topic_score_gemma":6.384046e-7,"domain_scores_codex":[0.9995161,0.00002015628,0.0001885321,0.00009404928,0.00008059185,0.000100518],"domain_scores_gemma":[0.9997451,0.00002211625,0.00001377569,0.0001459132,0.00003603766,0.00003707807],"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":[0.000003115227,0.000007769479,0.00002011185,0.00004379545,0.000009349324,0.000004277307,0.0001351034,0.9891793,0.002146843,0.0000145701,0.007178023,0.001257736],"study_design_scores_gemma":[0.0001121712,0.00001090201,0.000004850568,0.000005318531,0.000006804508,0.00004373892,0.00001626239,0.9729878,0.01836899,0.000005384068,0.008346423,0.00009137484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7162821,0.0003567377,0.2674498,0.00008187506,0.0005439453,0.0001789962,0.000006842099,0.003159706,0.01193999],"genre_scores_gemma":[0.9199243,0.00005604995,0.07567726,0.00000312449,0.00003955931,0.000005570044,0.00001918325,0.00002669555,0.004248272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2036422,"threshold_uncertainty_score":0.713078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009375299803195127,"score_gpt":0.2382573710986147,"score_spread":0.2288820712954195,"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."}}