{"id":"W4407242475","doi":"10.1016/j.seta.2025.104226","title":"Carbon Capture and Sequestration: Cutting-Edge Technologies to Combat Climate Change","year":2025,"lang":"en","type":"article","venue":"Sustainable Energy Technologies and Assessments","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Alberta; Delhi Technological University; All India Council for Technical Education","keywords":"Climate change; Carbon sequestration; Enhanced Data Rates for GSM Evolution; Climate change mitigation; Carbon capture and storage (timeline); Carbon fibers; Greenhouse gas; Environmental science; Natural resource economics; Engineering; Computer science; Carbon dioxide; Geology; Economics; Oceanography; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005932587,0.0007205349,0.0003484207,0.0009115418,0.0005681412,0.002015534,0.0004959877,0.001896652,0.005247847],"category_scores_gemma":[0.0006527882,0.0001551742,0.0002675688,0.0010461,0.001021994,0.001948712,0.0008119974,0.0009428953,0.0009715813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001105771,"about_ca_system_score_gemma":0.001629249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002082927,"about_ca_topic_score_gemma":0.003808378,"domain_scores_codex":[0.9995854,0.00005243587,0.00000790343,0.0000568336,0.0002432839,0.00005408416],"domain_scores_gemma":[0.9996929,0.0001110226,0.00003014393,0.00002103984,0.0001161765,0.00002874048],"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":[0.0002053421,0.0002727001,0.002401872,0.001336809,0.00008337345,0.000243565,0.0001213259,0.01677784,0.1024646,0.2716185,0.02068622,0.5837878],"study_design_scores_gemma":[0.0000478366,0.0006164395,0.005161532,0.0007248696,0.0001240497,0.0009084613,0.0005667201,0.07065007,0.3583973,0.184357,0.378326,0.0001196922],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.1142744,0.1757884,0.2817232,0.02698564,0.003758005,0.0002749781,0.0007837783,0.001065461,0.3953461],"genre_scores_gemma":[0.7901419,0.08527431,0.05871451,0.002602003,0.000885873,0.00008847573,0.0003956391,0.0001181149,0.06177913],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005247847,"threshold_uncertainty_score":0.01755583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006961167800513426,"score_gpt":0.2428617834810538,"score_spread":0.2359006156805404,"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."}}