{"id":"W2955946683","doi":"10.2172/828306","title":"REDUCING ULTRA-CLEAN TRANSPORTATION FUEL COSTS WITH HYMELT HYDROGEN","year":2004,"lang":"en","type":"report","venue":"","topic":"Coal Combustion and Slurry Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Procurement; Work (physics); Atmospheric pressure; Environmental science; Waste management; Engineering; Transport engineering; Nuclear engineering; Business; Mechanical engineering; Meteorology; Geography; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000170411,0.0003728298,0.0003792502,0.0001795143,0.00007386411,0.00007461982,0.0001343062,0.0002791112,0.0002949121],"category_scores_gemma":[0.00001451551,0.0003376728,0.0001025236,0.0002731744,0.00003069034,0.0001760733,0.000002075138,0.0004975389,0.00003240947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006565276,"about_ca_system_score_gemma":0.0004972826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003510855,"about_ca_topic_score_gemma":0.0009134762,"domain_scores_codex":[0.9982929,0.000008107832,0.0004333089,0.0003394439,0.0006212056,0.0003050412],"domain_scores_gemma":[0.9992986,0.00001779656,0.00009132698,0.0002583122,0.0001959614,0.0001380192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007614773,0.0001589677,0.000741253,0.01038251,0.0008661957,0.0005420444,0.003061636,0.6331977,0.003713082,0.000386287,0.009968786,0.3369054],"study_design_scores_gemma":[0.01013096,0.001118826,0.01544419,0.03038701,0.003582628,0.002412106,0.004338554,0.02011752,0.1738258,0.001204021,0.7207814,0.01665696],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05672798,0.003281347,0.01563408,0.00007337509,0.001157203,0.0006475524,0.00007322169,0.002730391,0.9196749],"genre_scores_gemma":[0.9938502,0.0009814457,0.0005866634,0.00002983103,0.0002190056,0.00001996489,0.0004287969,0.000142463,0.003741685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9371222,"threshold_uncertainty_score":0.9999076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01731556641572073,"score_gpt":0.239336752425822,"score_spread":0.2220211860101012,"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."}}