{"id":"W4400258907","doi":"10.2139/ssrn.4882478","title":"Structural Strength and Fatigue Analyses of Large-Scale Underwater Compressed Hydrogen Energy Storage Accumulator","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Spacecraft and Cryogenic Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Accumulator (cryptography); Underwater; Hydrogen storage; Energy storage; Environmental science; Compressive strength; Scale (ratio); Marine engineering; Structural engineering; Computer science; Materials science; Geology; Engineering; Metallurgy; Composite material; Physics; Oceanography; Algorithm","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0002595024,0.0004370069,0.0005834529,0.0003622692,0.00007574837,0.00009853246,0.0004850055,0.0004354399,0.000034598],"category_scores_gemma":[0.00001005439,0.0003658162,0.0002591814,0.0001640734,0.00008035194,0.00007264275,0.0005189527,0.003039724,0.00000169797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004903953,"about_ca_system_score_gemma":0.0004253525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000931789,"about_ca_topic_score_gemma":0.0009979133,"domain_scores_codex":[0.9973971,0.00004139252,0.0004589065,0.0003298176,0.0002799455,0.001492871],"domain_scores_gemma":[0.999317,0.00003307403,0.0001424041,0.0003757169,0.00005104004,0.00008075802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002250151,0.0001956979,0.002620577,0.002331929,0.02415301,0.0001414394,0.003029535,0.6787315,0.1783374,0.05884065,0.00272449,0.04866877],"study_design_scores_gemma":[0.001477023,0.0002597847,0.0003735952,0.0004364984,0.001243078,0.0004127433,0.004898634,0.3715743,0.1336749,0.4828187,0.001264465,0.001566182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9324516,0.05861599,0.007784536,0.0001024103,0.000412756,0.00008960076,0.00007001393,0.0003721795,0.0001008965],"genre_scores_gemma":[0.9909294,0.008368592,0.0001954815,0.000005601863,0.0001845753,0.00000928284,0.00003294121,0.00008042761,0.00019374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.423978,"threshold_uncertainty_score":0.9998794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02107869323081755,"score_gpt":0.2791226853483975,"score_spread":0.2580439921175799,"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."}}