{"id":"W4386697161","doi":"10.2172/1999387","title":"Electrical Infrastructure Cost Model for Marine Energy Systems","year":2023,"lang":"en","type":"report","venue":"","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Energy Efficiency; U.S. Department of Energy; Office of Energy Efficiency and Renewable Energy; Water Power Technologies Office; National Renewable Energy Laboratory; McMaster University","keywords":"Sizing; Flexibility (engineering); Offshore wind power; Wind power; Renewable energy; Scale (ratio); Cost estimate; Submarine pipeline; Engineering; Reliability engineering; Computer science; Systems engineering; Electrical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004704832,0.0009908378,0.0005487964,0.001316807,0.0004649123,0.001378065,0.001809305,0.001067421,0.01907697],"category_scores_gemma":[0.001695936,0.0004961683,0.001007327,0.001624678,0.0002576804,0.00190683,0.0006268295,0.0009938163,0.002700488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002471019,"about_ca_system_score_gemma":0.00213292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02920782,"about_ca_topic_score_gemma":0.02473972,"domain_scores_codex":[0.9995431,0.0001088629,0.00001964125,0.00005808903,0.0002008918,0.00006944647],"domain_scores_gemma":[0.9995404,0.0001837269,0.00004131968,0.00002923515,0.0001818479,0.00002349791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001006673,0.00001274364,0.0002846236,0.00003782563,0.00001003311,0.00004401265,0.00001222708,0.9662238,0.0002019379,0.0218906,0.004448248,0.006823863],"study_design_scores_gemma":[0.000009710643,0.00001633997,0.0003014535,0.00002014471,0.000008441195,0.00004192156,0.00002034484,0.9796823,0.0001568275,0.006856793,0.01287668,0.000009076763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04148431,0.001231167,0.6277537,0.001308374,0.0002144651,0.0004870115,0.01368209,0.001436385,0.3124025],"genre_scores_gemma":[0.7259634,0.00239012,0.08480424,0.00033393,0.0001224246,0.001489712,0.01151648,0.0008530691,0.1725267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02920782,"threshold_uncertainty_score":0.06381881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03598562294279147,"score_gpt":0.2807942124513009,"score_spread":0.2448085895085094,"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."}}