{"id":"W4237726819","doi":"10.1002/div.2913","title":"Imperial Oil Ltd.","year":2005,"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":"Petrochemical; Crude oil; Petroleum; Natural gas; Petroleum product; Barrel (horology); Oil refinery; Environmental science; Fossil fuel; Petroleum industry; Waste management; Petroleum engineering; Pulp and paper industry; Business; Engineering; Chemistry; Environmental engineering; Organic chemistry","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":[0.000216608,0.0001732099,0.0001575041,0.00009422876,0.00005959574,0.00003651983,0.0001863232,0.00007677762,0.0007536421],"category_scores_gemma":[0.00004785193,0.0001743918,0.0001028612,0.0001579125,0.00001508753,0.000201277,0.00002969531,0.0001589484,0.0002861744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007081173,"about_ca_system_score_gemma":0.000007642012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000808467,"about_ca_topic_score_gemma":0.000004875297,"domain_scores_codex":[0.9990696,0.00003099633,0.0002281074,0.0001555148,0.000216253,0.0002995378],"domain_scores_gemma":[0.9995341,0.00004506571,0.00001575442,0.0002482781,0.00001688,0.0001398667],"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":[0.000006000659,0.000009988,0.0003235809,0.00002425794,0.00004031668,0.000001750787,0.0001527116,0.9685642,0.006308626,0.0001226253,0.006954997,0.01749097],"study_design_scores_gemma":[0.0008117179,0.00001688829,0.001557094,0.00001980425,0.00002542008,0.000003146716,0.00002463085,0.3455408,0.01122248,0.00004566681,0.6403051,0.0004272087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706454,0.0007627244,0.01683312,0.0003089484,0.001970139,0.00004588481,0.000009978923,0.000748911,0.00867494],"genre_scores_gemma":[0.9817511,0.0003023934,0.01474013,0.00004646914,0.0007643909,0.00001410875,0.00001341974,0.00005066562,0.002317304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6333501,"threshold_uncertainty_score":0.8251852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373277173541416,"score_gpt":0.2508656363138587,"score_spread":0.2371328645784445,"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."}}