{"id":"W4416880243","doi":"10.37665/smveban37267","title":"Application of High Volume Manufacturing Practices to Fuel Cell Manufacturing","year":2008,"lang":"","type":"article","venue":"SMTA International","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Commercialization; Advanced manufacturing; Manufacturing cost; Fuel cells; Automation; Digital manufacturing; Production (economics); Manufacturing process","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002092376,0.0003697187,0.0003883221,0.0003196868,0.0001096308,0.00008223594,0.0006490985,0.0002841109,0.002100334],"category_scores_gemma":[0.0000412045,0.0003987575,0.0001425253,0.00008505107,0.0000640534,0.000437187,0.0002330297,0.0003383874,0.001120843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002125471,"about_ca_system_score_gemma":0.00004268844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008187021,"about_ca_topic_score_gemma":0.00001149382,"domain_scores_codex":[0.9976217,0.00003624955,0.0008472594,0.000508838,0.0005891824,0.0003968174],"domain_scores_gemma":[0.9985054,0.00008554931,0.0006874003,0.0004226538,0.0001223704,0.0001766277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004519749,0.0007873352,0.001405918,0.006196451,0.001087005,0.0001648913,0.003377352,0.8621177,0.1102995,0.0003199003,0.0064646,0.00732741],"study_design_scores_gemma":[0.0009581813,0.0001099568,0.01093201,0.0001561174,0.00008974663,0.00008681278,0.00009851735,0.01811479,0.8012612,0.0004398937,0.1670936,0.0006591075],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9228676,0.001438761,0.005883113,0.0008432927,0.007036691,0.0006843961,0.000194884,0.0001672121,0.06088405],"genre_scores_gemma":[0.9862017,0.003106165,0.005302662,0.0000629457,0.0008429685,0.00004244919,0.00008703009,0.00008003046,0.004274064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8440029,"threshold_uncertainty_score":0.9998465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021748634487683,"score_gpt":0.2231833405133044,"score_spread":0.2129658541684276,"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."}}