{"id":"W4360782622","doi":"10.2298/yjor221016004m","title":"A managerial approach in resource allocation models: An application in US and Canadian oil and gas companies","year":2023,"lang":"en","type":"article","venue":"Yugoslav journal of operations research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resource allocation; Planner; Data envelopment analysis; Novelty; Order (exchange); Environmental economics; Greenhouse gas; Resource (disambiguation); Computer science; Adaptation (eye); Perspective (graphical); Resource management (computing); Business; Industrial organization; Operations research; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002357219,0.001001563,0.0008762013,0.0008989704,0.001901617,0.002096547,0.001247594,0.001836861,0.00242517],"category_scores_gemma":[0.003871163,0.0003720782,0.0007200921,0.001909953,0.001174289,0.00076768,0.001075767,0.001297372,0.0001244125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009688646,"about_ca_system_score_gemma":0.007152091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3292801,"about_ca_topic_score_gemma":0.3483469,"domain_scores_codex":[0.9990588,0.0005396715,0.00002910744,0.00009943762,0.00013638,0.0001366712],"domain_scores_gemma":[0.9981831,0.001423316,0.0001009463,0.00004005938,0.0001873888,0.00006519006],"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":[0.00004661475,0.0001153996,0.001357491,0.00008478146,0.00002486222,0.0001256454,0.0002385204,0.9305725,0.0002966632,0.05309935,0.0005094864,0.01352869],"study_design_scores_gemma":[0.000015323,0.00003537917,0.0006178301,0.00001921554,0.00001497457,0.00001665868,0.0003007147,0.9894056,0.000119092,0.008144377,0.00129629,0.00001453269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4069022,0.002446024,0.5300107,0.003095679,0.000109792,0.0004642736,0.0003783023,0.0001632694,0.05642977],"genre_scores_gemma":[0.9297489,0.001006555,0.06302002,0.0001001389,0.00002580955,0.0002058626,0.0000620551,0.00001575071,0.005814791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6707199,"threshold_uncertainty_score":0.6547269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.203182646770192,"score_gpt":0.4388504875541352,"score_spread":0.2356678407839432,"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."}}