{"id":"W4238608442","doi":"10.2172/825602","title":"REDUCING ULTRA-CLEAN TRANSPORTATION FUEL COSTS WITH HYMELT HYDROGEN","year":2004,"lang":"en","type":"report","venue":"","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Environmental science; Work (physics); Nuclear engineering; Engineering; Waste management; Mechanical engineering; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002437759,0.0002044744,0.0001218202,0.0003564471,0.0002363507,0.0004189682,0.0005151719,0.0002340747,0.01030328],"category_scores_gemma":[0.0002919507,0.00007237882,0.0001902442,0.0003539248,0.0000935854,0.0008972744,0.0003451974,0.0003110437,0.001710152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004186266,"about_ca_system_score_gemma":0.0005532757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00154654,"about_ca_topic_score_gemma":0.005036068,"domain_scores_codex":[0.9998159,0.00001602259,0.000004805325,0.00001721776,0.0001200661,0.00002607787],"domain_scores_gemma":[0.9999032,0.0000147127,0.00001901641,0.00001605599,0.00003680238,0.0000101331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001286,0.0007748277,0.008787689,0.00062635,0.00007274158,0.0003519884,0.0001693975,0.005364759,0.337738,0.01199858,0.02489196,0.6079377],"study_design_scores_gemma":[0.00006022778,0.0007465802,0.01136056,0.00003203191,0.00003718404,0.0003190537,0.000188581,0.004814615,0.8627184,0.001626995,0.118076,0.00001960949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7543424,0.004328227,0.0893638,0.003449764,0.0004503829,0.0005028814,0.003039734,0.002062367,0.1424605],"genre_scores_gemma":[0.876474,0.002636119,0.05024055,0.0002668834,0.00005756273,0.0001722956,0.003092893,0.0002772191,0.06678257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01030328,"threshold_uncertainty_score":0.03446794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687675171834894,"score_gpt":0.2411783492194164,"score_spread":0.2243015975010675,"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."}}