{"id":"W4361280168","doi":"10.1016/j.jclepro.2023.136901","title":"The contribution of carbon capture and storage to Canada's net-zero plan","year":2023,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Carbon capture and storage (timeline); Environmental science; Natural gas; Carbon tax; Enhanced oil recovery; Fossil fuel; Natural resource economics; Environmental engineering; Business; Waste management; Greenhouse gas; Environmental protection; Engineering; Climate change; Economics; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003602888,0.00007839143,0.0001503611,0.0001171732,0.00002151635,0.00001324311,0.00009448974,0.00005606671,4.014721e-7],"category_scores_gemma":[0.000395073,0.00005654879,0.00002408702,0.0002413574,0.00002969002,0.00004061157,0.00001997888,0.0002224329,2.042139e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001448147,"about_ca_system_score_gemma":0.00004735528,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003514281,"about_ca_topic_score_gemma":0.03848302,"domain_scores_codex":[0.9993095,0.00001722245,0.000247053,0.00006945909,0.0002219345,0.0001348094],"domain_scores_gemma":[0.9995283,0.00003955677,0.0001039925,0.0001442311,0.0001443266,0.00003952909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002465354,0.00001452041,0.002754437,0.0001141131,0.0002646385,0.00009816736,0.001120062,0.5414445,0.2712395,0.000468196,0.1418244,0.04041093],"study_design_scores_gemma":[0.001460882,0.000499938,0.1235326,0.0003778912,0.0002448265,0.001295132,0.006576632,0.008208466,0.5387579,0.002567538,0.3156483,0.0008298971],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938994,0.0009659763,0.0000632707,0.003432527,0.001366688,0.0001088073,0.000002385219,0.00008315646,0.00007781335],"genre_scores_gemma":[0.9994833,0.0001876348,0.0000229945,0.00001288538,0.0001981685,0.000001862382,0.000001133755,0.00001208922,0.00007989179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.533236,"threshold_uncertainty_score":0.9790621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005764136582125505,"score_gpt":0.1867366444780696,"score_spread":0.1809725078959441,"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."}}