{"id":"W3209241420","doi":"10.3390/en14216957","title":"How CO2-to-Diesel Technology Could Help Reach Net-Zero Emissions Targets: A Canadian Case Study","year":2021,"lang":"en","type":"article","venue":"Energies","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Environmental economics; Diesel fuel; Renewable energy; Carbon price; Carbon neutrality; Greenhouse gas; Cost of electricity by source; Leverage (statistics); Carbon capture and storage (timeline); Natural resource economics; Environmental science; Electricity generation; Economics; Engineering; Computer science; Waste management; Climate change","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009434336,0.0003273893,0.0003955689,0.0006950144,0.0001102292,0.0001252602,0.0003582948,0.0003548135,0.00003223914],"category_scores_gemma":[0.0005440149,0.0003358331,0.00007004059,0.001250064,0.00009690481,0.0001072032,0.0002227193,0.0004994155,0.00001646087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000331133,"about_ca_system_score_gemma":0.0001791091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01263939,"about_ca_topic_score_gemma":0.2123939,"domain_scores_codex":[0.9984866,0.00002536999,0.0002245489,0.0004185569,0.0001882506,0.000656689],"domain_scores_gemma":[0.998565,0.0000644234,0.00002587745,0.0009530607,0.0001431865,0.0002484194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001976443,0.0003565316,0.01296283,0.0002228628,0.001324935,0.1620547,0.008912204,0.1774657,0.1893423,0.01253235,0.4033722,0.03143375],"study_design_scores_gemma":[0.001321977,0.0003145641,0.0007698066,0.0001444089,0.0001928362,0.007631425,0.1981841,0.002044289,0.2099197,0.002276892,0.5750479,0.002152137],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835245,0.005794,0.0001947671,0.004782789,0.0005677119,0.0002944677,0.00004875832,0.002974241,0.001818771],"genre_scores_gemma":[0.9958497,0.0001055295,0.002025452,0.0001168227,0.00006091755,0.000203444,0.00001239091,0.00007562039,0.001550081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1997545,"threshold_uncertainty_score":0.9999093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01122732375162302,"score_gpt":0.2209893260443037,"score_spread":0.2097620022926806,"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."}}