{"id":"W4235370587","doi":"10.1002/div.5820","title":"Ensign Energy Services Inc","year":2007,"lang":"en","type":"article","venue":"Mergent s Dividend Achievers","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"General partnership; Fossil fuel; Drilling; Service (business); Engineering; Business; Waste management; Finance; 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":[0.0004373698,0.0001870378,0.0001624987,0.0001644664,0.00006406067,0.00002963566,0.0002050763,0.00009355344,0.00020083],"category_scores_gemma":[0.00001269423,0.0001889984,0.00007505502,0.000250093,0.00001394037,0.0001661984,0.00003661777,0.0001295311,0.00005872541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005066389,"about_ca_system_score_gemma":0.000004675276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000758553,"about_ca_topic_score_gemma":0.00004068695,"domain_scores_codex":[0.9989221,0.00002738355,0.0002667029,0.0001671851,0.0002531349,0.0003635114],"domain_scores_gemma":[0.9994302,0.0001004533,0.00002317193,0.0002553545,0.00002193333,0.0001688253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001074401,0.00001307316,0.002191763,0.00007155324,0.00007636675,0.00001557346,0.0002052426,0.9823546,0.006472724,0.001136548,0.001445916,0.006005924],"study_design_scores_gemma":[0.0009201875,0.00004691294,0.01844549,0.0000638836,0.00005333087,0.000007836102,0.0002129475,0.40021,0.03789441,0.0008450493,0.5403963,0.0009037027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5576676,0.00115135,0.4316628,0.000062317,0.001818779,0.00007099025,0.000007012291,0.0008510387,0.006708135],"genre_scores_gemma":[0.9925444,0.000159771,0.006506992,0.00007846968,0.0002096045,0.000004368856,0.00002408649,0.00004691057,0.0004254695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5821446,"threshold_uncertainty_score":0.7707129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009608738782639,"score_gpt":0.2360726944467835,"score_spread":0.2259766070589571,"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."}}