{"id":"W4241359968","doi":"10.1016/s1464-2859(05)00565-1","title":"Nissan in-house stack with Dynetek hydrogen storage system","year":2005,"lang":"en","type":"article","venue":"Fuel Cells Bulletin","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stack (abstract data type); Hydrogen storage; Fuel cells; Automotive engineering; Automotive industry; Engineering; Bar (unit); Hydrogen; Mechanical engineering; Computer science; Operating system; Chemistry; Physics; Aerospace engineering; Chemical engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001913236,0.0002853204,0.000330333,0.0001081963,0.00003813272,0.00005938818,0.0001973438,0.0001887944,0.0008071013],"category_scores_gemma":[0.000002122264,0.0002412621,0.00004998975,0.0001364972,0.0000358432,0.00004396083,0.00003315934,0.0002394167,0.003591776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001625999,"about_ca_system_score_gemma":0.00001464187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005431559,"about_ca_topic_score_gemma":0.00003173041,"domain_scores_codex":[0.9986531,0.00004737165,0.000360286,0.000272815,0.0001967515,0.0004696555],"domain_scores_gemma":[0.9994261,0.00003210943,0.00005050936,0.0003354313,0.00002153105,0.0001343773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000116907,0.0001445237,0.00007686584,0.005187952,0.0001338881,0.0006242512,0.001167864,0.9169151,0.0370463,0.00009363121,0.03823433,0.0002583882],"study_design_scores_gemma":[0.001480698,0.0001169883,0.00004157638,0.0003091233,0.00003918302,0.00004822018,0.0002738153,0.01359517,0.06036261,0.000005875715,0.9230317,0.000695027],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8476227,0.01062477,0.0001126771,0.0002850401,0.001043685,0.0008278569,0.00004724127,0.002372451,0.1370636],"genre_scores_gemma":[0.9962309,0.00075247,0.001165629,0.00005441642,0.000233987,0.00002849832,0.000007895167,0.0001680527,0.001358177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9033199,"threshold_uncertainty_score":0.997184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003692087002100108,"score_gpt":0.1580991171517795,"score_spread":0.1544070301496794,"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."}}