{"id":"W2323906322","doi":"10.1002/ese3.117","title":"The progressive routes for carbon capture and sequestration","year":2016,"lang":"en","type":"article","venue":"Energy Science & Engineering","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Carbon sequestration; Greenhouse gas; Greenhouse gas removal; Environmental science; Global warming; Fossil fuel; Bio-energy with carbon capture and storage; Carbon fibers; Biochar; Biofuel; Carbon capture and storage (timeline); Climate change mitigation; Climate change; Environmental protection; Waste management; Carbon dioxide; Chemistry; Ecology; Engineering; Pyrolysis; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001683829,0.0001241509,0.00008092536,0.00008920563,0.00004792333,0.00008447812,0.0002320369,0.00005935633,3.474301e-7],"category_scores_gemma":[0.0002186278,0.00007306262,0.00002051152,0.0002204202,0.0002010555,0.0002039291,0.00003914685,0.00005311288,1.688076e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009486652,"about_ca_system_score_gemma":0.00002241379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007527594,"about_ca_topic_score_gemma":0.000009816665,"domain_scores_codex":[0.9992587,0.000001960022,0.0001042642,0.000175401,0.0001418247,0.000317824],"domain_scores_gemma":[0.9995716,0.0001127228,0.00001796522,0.0002028379,0.00004552357,0.00004934813],"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":[0.000001497885,9.827478e-7,0.00005210726,0.000002790777,0.000007146115,0.000001973866,0.00005669976,0.01108884,0.5835351,0.3992416,0.00002533766,0.005985987],"study_design_scores_gemma":[0.0002541709,0.00004206255,0.001033526,0.00008092087,0.00001080386,0.00002793916,0.0001131884,0.07278623,0.8918417,0.001568338,0.03184856,0.000392518],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9410164,0.007164742,0.04612635,0.0009128461,0.001177435,0.0002910798,0.000006878563,0.002400051,0.0009041902],"genre_scores_gemma":[0.9983637,0.00008112715,0.001300097,0.000005372447,0.00006983723,0.0001052254,3.2142e-7,0.00001849673,0.00005576995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3976732,"threshold_uncertainty_score":0.2979407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003984608838305081,"score_gpt":0.1833899750881965,"score_spread":0.1794053662498914,"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."}}