{"id":"W4238076008","doi":"10.2172/1361459","title":"Next Generation Hydrogen Station Composite Data Products: Retail Stations, Data through Quarter 4 of 2016","year":2017,"lang":"en","type":"report","venue":"","topic":"Transportation Systems and Infrastructure","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Composite number; Business; Telecommunications; Database; Commerce; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001055117,0.0003915273,0.0006136714,0.0002124643,0.0003196014,0.0007759907,0.001809672,0.0002611818,0.0007600621],"category_scores_gemma":[0.0002079364,0.0003273904,0.00005551947,0.0002085067,0.00008225413,0.0107673,0.0003336616,0.000228218,0.0001280475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004306897,"about_ca_system_score_gemma":0.0007608988,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01164401,"about_ca_topic_score_gemma":0.002385522,"domain_scores_codex":[0.9962692,0.00002357423,0.001266661,0.001090005,0.001104313,0.0002462688],"domain_scores_gemma":[0.9912063,0.00001929886,0.002601494,0.004477687,0.00168231,0.00001293479],"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":[0.00001666985,0.00004890141,0.003112714,0.001635358,0.0002363285,0.000005201553,0.00008324089,0.00004894865,0.001608187,0.000643004,0.9859692,0.006592189],"study_design_scores_gemma":[0.0003697867,0.000007579566,0.004905461,0.000269449,0.0003952022,0.000004157092,0.0001700059,0.004009936,0.00007525241,0.0001834994,0.9891812,0.0004284719],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.05122668,0.0169725,0.08040205,0.01191259,0.02889452,0.01400344,0.05164018,0.001616102,0.743332],"genre_scores_gemma":[0.2765695,0.001870744,0.01132664,0.0006208995,0.01533402,0.00005179933,0.6753511,0.0002114583,0.01866378],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7246681,"threshold_uncertainty_score":0.9999178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1883175916008341,"score_gpt":0.3198767456958416,"score_spread":0.1315591540950075,"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."}}