{"id":"W1593822039","doi":"10.4271/2005-01-3770","title":"A Fuel Quality Sensor for Fuel Cell Vehicles, Natural Gas Vehicles, and Variable Gaseous Fuel Vehicles","year":2005,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fuel cells; Automotive engineering; Green vehicle; Miles per gallon gasoline equivalent; Natural gas; Variable (mathematics); Quality (philosophy); Environmental science; Fuel efficiency; Computer science; Waste management; Engineering; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003006376,0.000565346,0.0004772398,0.0008972359,0.0004160292,0.0008315195,0.0008676247,0.001242875,0.0107117],"category_scores_gemma":[0.000562132,0.0002749615,0.0003124126,0.0009109231,0.0002624574,0.001160656,0.0003166859,0.0006512409,0.003750471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007311549,"about_ca_system_score_gemma":0.0005336234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001441003,"about_ca_topic_score_gemma":0.001687412,"domain_scores_codex":[0.9994276,0.00007100586,0.00002141487,0.00008371739,0.0003718469,0.00002440384],"domain_scores_gemma":[0.9996803,0.00005911261,0.00002178048,0.00002655368,0.0001841489,0.00002818469],"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":[0.0004155102,0.000239542,0.002609063,0.0007689938,0.00005237587,0.0003857006,0.0001314916,0.004120713,0.4803967,0.01788067,0.04755815,0.4454411],"study_design_scores_gemma":[0.00009300192,0.0009931208,0.0056822,0.0001163143,0.0000823341,0.001539843,0.0001509778,0.09828789,0.4752771,0.004172239,0.4134973,0.0001077482],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04355493,0.008977666,0.8363327,0.002322984,0.002459538,0.001025812,0.003274519,0.01323414,0.08881781],"genre_scores_gemma":[0.39539,0.006001585,0.436653,0.002048004,0.000729378,0.000657069,0.005270001,0.0005988892,0.152652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0107117,"threshold_uncertainty_score":0.03583419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213923910462817,"score_gpt":0.2652628202017776,"score_spread":0.2531235810971494,"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."}}