{"id":"W4401442294","doi":"10.1038/s41467-024-50040-6","title":"Offshore wind and wave energy can reduce total installed capacity required in zero-emissions grids","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Wave and Wind Energy Systems","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"Water Power Technologies Office; U.S. Department of Energy; National Science Foundation","keywords":"Offshore wind power; Submarine pipeline; Environmental science; Zero emission; Greenhouse gas; Energy (signal processing); Wind power; Marine engineering; Meteorology; Physics; Geology; Oceanography; Engineering; Electrical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0001333056,0.0001615609,0.0001829588,0.0001842317,0.0001259373,0.00006581898,0.000305834,0.0003571713,0.000007509514],"category_scores_gemma":[0.00004519174,0.0001537984,0.00005186042,0.000462805,0.00008455752,0.0001327699,0.0001535613,0.0008368728,0.000002547013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001236794,"about_ca_system_score_gemma":0.00005065808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002825043,"about_ca_topic_score_gemma":0.001661084,"domain_scores_codex":[0.9991763,0.00007313299,0.0002509215,0.0001787252,0.0001175349,0.0002033589],"domain_scores_gemma":[0.9987506,0.0001322235,0.00001607674,0.0009608205,0.00003404237,0.0001062452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003943741,0.0004559839,0.002082498,0.00069737,0.001059379,0.0001597871,0.0234789,0.01839918,0.1805573,0.568136,0.154208,0.05072618],"study_design_scores_gemma":[0.0008852699,0.00005874027,0.0145444,0.001239451,0.00009411987,0.0003178079,0.001047149,0.1787306,0.006089895,0.003873625,0.7919246,0.001194364],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8531192,0.06039735,0.000202688,0.005821615,0.00157891,0.000286265,0.000201476,0.0008937443,0.07749876],"genre_scores_gemma":[0.9972993,0.001088902,0.0005576912,0.00005422844,0.00009460649,0.00002716361,0.0001306329,0.00003556589,0.0007119012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6377165,"threshold_uncertainty_score":0.6271717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02559661898018896,"score_gpt":0.2492642169054923,"score_spread":0.2236675979253034,"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."}}