{"id":"W2944230795","doi":"10.2172/1510711","title":"Next Generation Hydrogen Station Composite Data Products: Retail Stations, Data through Quarter 4 of 2018","year":2019,"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); Composite number; Environmental science; Telecommunications; Business; Database; Computer science; 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":[0.001033449,0.001028048,0.0004571697,0.002422313,0.0005426239,0.0025939,0.0008999655,0.0005559217,0.08082421],"category_scores_gemma":[0.005047509,0.0005222594,0.0004217892,0.005138148,0.0001972104,0.001984043,0.0008048083,0.001080222,0.07763357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002045193,"about_ca_system_score_gemma":0.005426922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05942325,"about_ca_topic_score_gemma":0.05169648,"domain_scores_codex":[0.9987051,0.00004260466,0.00008187458,0.00009451428,0.0009793364,0.00009651868],"domain_scores_gemma":[0.9963168,0.0003191782,0.0002882899,0.0001782802,0.00272425,0.0001732436],"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":[0.000104165,0.00004061604,0.001755742,0.0001431932,0.00001003072,0.00001293658,0.00001917498,0.0002524758,0.0002060726,0.0006134908,0.984378,0.01246415],"study_design_scores_gemma":[0.00005197033,0.00005529485,0.01229886,0.00009389965,0.00001794165,0.00002244874,0.0001121768,0.0003889372,0.001680125,0.0003960274,0.9848637,0.00001866015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002633392,0.0003025243,0.0006950222,0.0006192962,0.0005605786,0.0001670632,0.9309891,0.0007188118,0.06331421],"genre_scores_gemma":[0.00604331,0.0009371503,0.001389315,0.0001991453,0.0001182688,0.0003148886,0.8908845,0.0005271448,0.09958638],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08082421,"threshold_uncertainty_score":0.2703839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2222614075140514,"score_gpt":0.3325332192489461,"score_spread":0.1102718117348947,"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."}}