{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001719322,0.0003582677,0.0001577255,0.0006513573,0.001624708,0.001471044,0.0003884703,0.0007342975,0.1375022],"category_scores_gemma":[0.000236405,0.0002101739,0.0001322069,0.0006142503,0.0002393133,0.0004600846,0.0007396794,0.0006595778,0.04402294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001359692,"about_ca_system_score_gemma":0.002934475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04775991,"about_ca_topic_score_gemma":0.1216076,"domain_scores_codex":[0.9998061,0.000006894912,0.000003602984,0.00002791888,0.0001178247,0.0000376232],"domain_scores_gemma":[0.9996898,0.000009971972,0.00001497843,0.00002236753,0.0001824417,0.00008041623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002064758,0.000179457,0.001468612,0.0001222015,0.000006633837,0.0004749391,0.00005360783,0.0005794183,0.01041949,0.009479941,0.8852257,0.09178358],"study_design_scores_gemma":[0.00001951621,0.00004315967,0.001622359,0.00002588828,0.000003618174,0.000105033,0.00003789805,0.000770898,0.003255565,0.0004849089,0.9936232,0.000007987377],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01556582,0.001101784,0.002213017,0.003754903,0.001164357,0.0001027197,0.004184464,0.001530807,0.9703821],"genre_scores_gemma":[0.03765897,0.001113162,0.001883819,0.0006221537,0.0001370342,0.00004339579,0.002704835,0.0001154661,0.9557211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1375022,"threshold_uncertainty_score":0.4599906,"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."}}