{"id":"W7002284975","doi":"","title":"Missouri S&T Hydrogen Fuel Cell EcoCAR","year":2009,"lang":"en","type":"other","venue":"MOspace Institutional Repository (University of Missouri)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrogen fuel; Hydrogen economy; Automotive industry; Hydrogen vehicle; Steam reforming; Natural gas; Fuel cells; Renewable energy; Greenhouse gas","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":[0.0001175184,0.0003364758,0.0003357054,0.00012448,0.0002613296,0.00001729181,0.0005793321,0.0006604703,0.0002940242],"category_scores_gemma":[0.0000375538,0.0004197563,0.0002793358,0.0001039282,0.0003469665,0.00000762019,0.0001870567,0.0002924667,0.0001305736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007343489,"about_ca_system_score_gemma":0.0003473288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004002877,"about_ca_topic_score_gemma":0.0001996436,"domain_scores_codex":[0.9986551,0.0000725178,0.000190902,0.0004208772,0.0003906208,0.0002700067],"domain_scores_gemma":[0.9985886,0.00001011369,0.0004893053,0.0006331784,0.00009569019,0.0001830631],"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":[0.0001734956,0.0003423205,0.001108504,0.0008164604,0.0004356928,0.0001687743,0.0004816037,0.004475242,0.0228076,0.0002499059,0.9685551,0.0003852871],"study_design_scores_gemma":[0.0005894874,0.0001216632,0.0002252278,0.0001295865,0.00009907598,0.0000943605,0.0001047066,0.0001452818,0.001588443,0.00001749932,0.9964633,0.0004213979],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01569901,0.004006261,0.001746231,0.0002033324,0.0002829421,0.0002750191,0.00009548662,0.0000958421,0.9775959],"genre_scores_gemma":[0.02317879,0.0006192632,0.01297395,0.00009692543,0.000452046,4.455239e-7,0.0005365877,0.0001105741,0.9620314],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02790816,"threshold_uncertainty_score":0.9998254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004902975563084963,"score_gpt":0.1888889824212202,"score_spread":0.1839860068581352,"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."}}