{"id":"W1978139091","doi":"10.2118/124235-ms","title":"Minimizing Environmental Footprint by Utilizing Prevention Technology","year":2009,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Marine and Offshore Engineering Studies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"License; Environmental stewardship; Profitability index; Greenhouse gas; Stewardship (theology); Environmental economics; Ecological footprint; Environmental impact assessment; Business; Natural resource economics; Environmental resource management; Environmental science; Computer science; Sustainable development; Finance; 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":[0.0005287543,0.0005783105,0.0003987749,0.001256593,0.0007024324,0.00178235,0.001294074,0.001012233,0.005565996],"category_scores_gemma":[0.001090685,0.0002065093,0.0004979536,0.0006644868,0.000996857,0.001935578,0.00132436,0.0005966984,0.001168513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005428849,"about_ca_system_score_gemma":0.0009447388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001193958,"about_ca_topic_score_gemma":0.00188587,"domain_scores_codex":[0.9992509,0.0001311845,0.00003488404,0.00007365624,0.000410594,0.0000987127],"domain_scores_gemma":[0.9987158,0.0004617191,0.0002150047,0.0002437668,0.0003035953,0.00006017993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003996992,0.001396502,0.01782519,0.001544619,0.00009306922,0.001168072,0.0007870447,0.02423627,0.2518291,0.09084635,0.006947016,0.602927],"study_design_scores_gemma":[0.0001580835,0.002753844,0.01239576,0.0005131802,0.0004079542,0.00325381,0.001739273,0.07570837,0.701721,0.07370085,0.1274735,0.0001743309],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4084495,0.004661499,0.4231877,0.004032093,0.0004395407,0.0003921907,0.0002058839,0.002883341,0.1557482],"genre_scores_gemma":[0.94343,0.001345938,0.03987836,0.000310852,0.00004350707,0.00007845848,0.00009008496,0.00005583499,0.01476688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005565996,"threshold_uncertainty_score":0.01862013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009363255774059907,"score_gpt":0.2220104987999264,"score_spread":0.2126472430258665,"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."}}