{"id":"W4417242494","doi":"10.1039/d5se01118c","title":"Impact of background systems on carbon capture and utilization pathways to produce fuels/chemicals in Canada","year":2025,"lang":"en","type":"article","venue":"Sustainable Energy & Fuels","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto","funders":"Natural Resources Canada; Canada Research Chairs","keywords":"Greenhouse gas; Climate change; Carbon fibers; Climate change mitigation; Global warming; Carbon capture and storage (timeline); Life-cycle assessment; Sustainability","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001317776,0.0002613067,0.0004075553,0.0004026857,0.0000138442,0.00003229754,0.0001985455,0.0001711646,0.000002739692],"category_scores_gemma":[0.0001823144,0.0002503115,0.0000397679,0.0009939919,0.00002956653,0.00007127233,0.0000939667,0.0001768827,1.04314e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002426025,"about_ca_system_score_gemma":0.0006429001,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6105238,"about_ca_topic_score_gemma":0.1497687,"domain_scores_codex":[0.9986266,0.00002611817,0.0003342284,0.0003236087,0.0001941993,0.000495223],"domain_scores_gemma":[0.9991836,0.00008413048,0.00004630551,0.0004681854,0.0001437641,0.0000740071],"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":[0.0002075705,0.0001040745,0.01283096,0.004131706,0.0003769624,0.0004216599,0.0008476651,0.572016,0.2938159,0.101525,0.008053114,0.005669348],"study_design_scores_gemma":[0.002556828,0.000503061,0.03652561,0.001525502,0.0001297423,0.00003291831,0.03866581,0.01884121,0.8745105,0.009920548,0.01438502,0.002403249],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868791,0.004888243,0.0001056981,0.00006385184,0.0001787326,0.0003153971,0.000012325,0.0001834695,0.007373166],"genre_scores_gemma":[0.9992492,0.0001103098,0.00001782548,0.00003075675,0.00002205072,0.0000935582,0.000009722158,0.00003227999,0.0004343014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5806946,"threshold_uncertainty_score":0.9999949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009488731413570279,"score_gpt":0.2182969714556077,"score_spread":0.2088082400420374,"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."}}