{"id":"W3095227349","doi":"10.1016/j.jclepro.2020.124980","title":"Mitigating greenhouse gas intensity through new generation techniques during heavy oil recovery","year":2020,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Steam injection; Environmental science; Waste management; Environmentally friendly; Process engineering; Natural gas; Petroleum engineering; Fossil fuel; Enhanced oil recovery; Limiting; Engineering; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001480304,0.0002218824,0.0001450139,0.0002536546,0.0002173456,0.0003125267,0.0002705844,0.0002342495,0.001101648],"category_scores_gemma":[0.00019574,0.00008364722,0.00017549,0.0001975544,0.0001715295,0.0005159419,0.0002164229,0.0003200346,0.0001995839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002020718,"about_ca_system_score_gemma":0.0002048252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005815438,"about_ca_topic_score_gemma":0.002145744,"domain_scores_codex":[0.9999206,0.000009311891,0.000002642116,0.00001293427,0.00003510894,0.00001929993],"domain_scores_gemma":[0.9998957,0.00002867865,0.000026363,0.00001073051,0.00003274705,0.00000578952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004366515,0.00009973015,0.002528231,0.0002325759,0.00001840998,0.0002095504,0.0001083678,0.008491108,0.9211227,0.001495025,0.0003660928,0.06489153],"study_design_scores_gemma":[0.00001717432,0.0004168423,0.003972915,0.00001663783,0.00003502686,0.000140931,0.000167612,0.02260134,0.9666727,0.000762754,0.005182243,0.00001385119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9234042,0.001250872,0.06720089,0.0002874772,0.00008798234,0.00004907488,0.00009516118,0.0002220194,0.007402306],"genre_scores_gemma":[0.991044,0.0004221336,0.006349241,0.00002615729,0.00001072672,0.000009770939,0.00002516715,0.00001471109,0.002097984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001101648,"threshold_uncertainty_score":0.003685355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02314277460253032,"score_gpt":0.2335224974305466,"score_spread":0.2103797228280163,"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."}}