{"id":"W4399615955","doi":"10.1016/j.geoen.2024.213032","title":"Introduction of a carbon footprint assessment in the oil and gas facility life extension decision-making process","year":2024,"lang":"en","type":"article","venue":"Geoenergy Science and Engineering","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Carbon footprint; Life extension; Extension (predicate logic); Process (computing); Life-cycle assessment; Decision-making; Environmental science; Fossil fuel; Engineering; Waste management; Greenhouse gas; Process engineering; Computer science; Production (economics); Medicine; Economics; Process integration; Gerontology; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.007251129,0.001230444,0.0007222529,0.00176416,0.00155239,0.008054738,0.001862293,0.00472487,0.01379079],"category_scores_gemma":[0.01199248,0.0007689097,0.001664195,0.001774281,0.002006565,0.005206327,0.002661576,0.00457914,0.003331071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003049341,"about_ca_system_score_gemma":0.00500845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007406129,"about_ca_topic_score_gemma":0.00761759,"domain_scores_codex":[0.9950824,0.001881712,0.0003637753,0.0005419468,0.001897319,0.0002328071],"domain_scores_gemma":[0.9887537,0.006109599,0.0004686335,0.0006739213,0.003541333,0.0004528037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001971687,0.0004040688,0.00290717,0.0009252792,0.0001146555,0.0005524575,0.0007620417,0.07821564,0.006145115,0.5151654,0.02821745,0.3663936],"study_design_scores_gemma":[0.00004257125,0.0003287431,0.002470695,0.001078891,0.00008330993,0.0004140525,0.00065473,0.250081,0.008860354,0.3336382,0.4021098,0.0002376645],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006447372,0.002246048,0.8859046,0.01161652,0.002153219,0.0006631963,0.0006894948,0.0006590901,0.08962045],"genre_scores_gemma":[0.111639,0.002687913,0.8528283,0.00179729,0.001760177,0.0004294856,0.0004872882,0.0003178012,0.02805273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01379079,"threshold_uncertainty_score":0.04613477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008498966277905648,"score_gpt":0.2746007876302431,"score_spread":0.2661018213523375,"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."}}