{"id":"W2121888083","doi":"10.1109/eicccc.2006.277263","title":"Economic Aspects of Greenhouse Gas Emissions Reduction by Utilisation of Wind and Solar Energies to Produce Electricity and hydrogen","year":2006,"lang":"en","type":"article","venue":"","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Renewable energy; Greenhouse gas; Fossil fuel; Environmental science; Electricity generation; Electricity; Renewable fuels; Carbon-neutral fuel; Natural gas; Waste management; Cost of electricity by source; Environmental engineering; Engineering; Hydrogen; Chemistry; Power (physics); Syngas","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":[0.0001867002,0.0001429997,0.0002680653,0.0001532165,0.00006024266,0.00001454906,0.00007148351,0.00007509118,0.00002781273],"category_scores_gemma":[0.00003411793,0.0001335054,0.00003010943,0.0001518654,0.00005875769,0.0001538757,0.00003731634,0.00004125222,0.000001847745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006920693,"about_ca_system_score_gemma":0.00006107421,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0416396,"about_ca_topic_score_gemma":0.002876488,"domain_scores_codex":[0.9989103,0.00007286404,0.0003901581,0.0003292141,0.0001168231,0.0001806517],"domain_scores_gemma":[0.9994369,0.00003224738,0.0001614355,0.0002485565,0.00004228469,0.00007857431],"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":[0.00003276824,0.00007180339,0.001747291,0.00004180442,0.00004062998,6.143291e-7,0.0001373115,0.07652518,0.9109298,0.005109867,0.002411675,0.002951251],"study_design_scores_gemma":[0.0002624789,0.0001116665,0.0009949335,0.00002022562,0.00002209842,0.00002570175,0.00008640301,0.001985845,0.9916527,0.0007928445,0.003902577,0.0001424721],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910444,0.0004108631,0.00008136602,0.0001204783,0.00006075832,0.0001508318,0.000008786101,0.00005451923,0.00806802],"genre_scores_gemma":[0.9973019,0.00006856152,0.0001941246,0.00000535765,0.0001210725,0.000006980252,0.00001823614,0.0000238966,0.002259823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08072295,"threshold_uncertainty_score":0.9647422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006630120482296894,"score_gpt":0.2014753438167681,"score_spread":0.1948452233344712,"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."}}