{"id":"W2916897783","doi":"10.2172/1455119","title":"Next Generation Hydrogen Station Composite Data Products: Retail Stations, Data through Quarter 4 of 2017","year":2018,"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; Geography; Materials science; Composite material; Archaeology","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":[0.0009287963,0.001098459,0.0004784844,0.002691026,0.0006001748,0.002661257,0.00101938,0.0005557225,0.06591469],"category_scores_gemma":[0.004802502,0.0005594422,0.0004337338,0.005200137,0.0002088417,0.002166219,0.0008200696,0.00107843,0.0658356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002250446,"about_ca_system_score_gemma":0.00615819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06024511,"about_ca_topic_score_gemma":0.05481921,"domain_scores_codex":[0.9984373,0.00004371231,0.00008760986,0.000103728,0.001216178,0.0001114913],"domain_scores_gemma":[0.9960219,0.0003094288,0.00032282,0.0002070719,0.002966065,0.0001726119],"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":[0.0001310997,0.00006189269,0.00314921,0.0001455311,0.00001357341,0.00001913649,0.0000266415,0.0003881306,0.0002515181,0.000766771,0.9815536,0.01349289],"study_design_scores_gemma":[0.00006495139,0.00007768343,0.0195862,0.00009859406,0.00002434783,0.00003356667,0.0001970305,0.0005745448,0.003238615,0.0005340929,0.9755449,0.00002548849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004053943,0.0002753625,0.0007317687,0.0005625246,0.0005457973,0.0001893703,0.929655,0.0007342486,0.06325193],"genre_scores_gemma":[0.007462861,0.0008122248,0.001100775,0.0001511467,0.0001158507,0.000294328,0.9005138,0.0004718208,0.0890773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06591469,"threshold_uncertainty_score":0.2205066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2688098398553629,"score_gpt":0.3517522885109843,"score_spread":0.08294244865562139,"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."}}