{"id":"W3091980650","doi":"10.2172/1669431","title":"Next Generation Hydrogen Station Composite Data Products: Retail Stations (Data through Quarter 3 of 2019)","year":2020,"lang":"en","type":"report","venue":"","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Software deployment; Reliability (semiconductor); Composite number; Data quality; Hydrogen production; Environmental science; Hydrogen; Computer science; Engineering; Operations management; Chemistry; Operating system; 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":[0.001727501,0.001209257,0.0005723613,0.002598222,0.000390207,0.002495162,0.001007691,0.0007024974,0.07489278],"category_scores_gemma":[0.005674755,0.0005845922,0.000671697,0.006431472,0.0001699458,0.001965533,0.0009075938,0.001108328,0.08779901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001988182,"about_ca_system_score_gemma":0.005320108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05421177,"about_ca_topic_score_gemma":0.0401553,"domain_scores_codex":[0.9984049,0.00007572101,0.0001191792,0.0001230478,0.00114044,0.0001367891],"domain_scores_gemma":[0.993296,0.0005344917,0.0004804403,0.0003071913,0.005110489,0.00027149],"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":[0.0001343484,0.00004018045,0.001680881,0.0002878612,0.00001667799,0.00001387168,0.00001769146,0.0004850277,0.000370824,0.0008284709,0.9796285,0.0164957],"study_design_scores_gemma":[0.00004919515,0.00007561743,0.01383177,0.0001362736,0.00002349416,0.00002274172,0.00008253344,0.0005547799,0.00162758,0.0004333416,0.9831328,0.00002991202],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001223752,0.0002162799,0.0008667331,0.0003416383,0.0004733029,0.000114482,0.9636186,0.0006229684,0.0325223],"genre_scores_gemma":[0.004338358,0.000551136,0.001896415,0.0001737188,0.00007188453,0.0002549665,0.9544685,0.0003667275,0.03787828],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07489278,"threshold_uncertainty_score":0.2505413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2142749729234893,"score_gpt":0.3289650136189408,"score_spread":0.1146900406954515,"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."}}