{"id":"W4233455434","doi":"10.1002/div.5385","title":"Ensign Energy Services Inc","year":2006,"lang":"en","type":"article","venue":"Mergent s Dividend Achievers","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drilling; Fossil fuel; Environmental science; Engineering; Waste management; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001427375,0.0001882485,0.0001639257,0.0001226856,0.00006369109,0.00004123157,0.0001849099,0.0000803785,0.0002058866],"category_scores_gemma":[0.000004985967,0.0001900586,0.00007636594,0.0002058056,0.00001314926,0.0001673886,0.00003157007,0.0001012701,0.00006010895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004170215,"about_ca_system_score_gemma":0.000004795382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003237679,"about_ca_topic_score_gemma":0.00004824461,"domain_scores_codex":[0.999045,0.00003871847,0.0002385078,0.0001676504,0.0002255576,0.0002845232],"domain_scores_gemma":[0.9995805,0.00005362982,0.00002220343,0.0002418769,0.00001865553,0.0000831513],"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":[0.000003083179,0.00001082833,0.001623006,0.00004735298,0.00003075978,0.000005444616,0.00003314894,0.9881965,0.003864251,0.001525867,0.00382055,0.0008392063],"study_design_scores_gemma":[0.0005617191,0.00001976082,0.01017658,0.00003403994,0.00003439496,0.000003396909,0.00003514996,0.6216117,0.01220591,0.001691673,0.3530795,0.0005461203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7880144,0.002248779,0.1936277,0.0001481883,0.001988357,0.000104966,0.00002057597,0.001414778,0.01243229],"genre_scores_gemma":[0.9942483,0.0001060388,0.004395503,0.00004142344,0.0002606518,0.00001183701,0.00005515086,0.00004708964,0.0008339558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3665848,"threshold_uncertainty_score":0.7750365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006625044932552884,"score_gpt":0.2047893033046908,"score_spread":0.1981642583721379,"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."}}