{"id":"W2778900361","doi":"10.1177/0309524x18756962","title":"On mooring line tension and fatigue prediction for offshore vertical axis wind turbines: A comparison of lumped mass and quasi-static approaches","year":2018,"lang":"en","type":"article","venue":"Wind Engineering","topic":"Wave and Wind Energy Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Turbine; Marine engineering; Mooring; Offshore wind power; Wind power; Horizontal axis; Aerodynamics; Tension (geology); Vertical axis; Rotor (electric); Engineering; Structural engineering; Aerospace engineering; Compression (physics); Mechanical engineering; Physics; 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":[0.0001330994,0.000217421,0.0003487076,0.0001420412,0.00005093951,0.00002555024,0.00005582375,0.0001341726,0.000002068375],"category_scores_gemma":[0.00005748519,0.0002054276,0.00003943071,0.0001228514,0.00004157699,0.0001094211,0.00001817954,0.0001276333,9.666837e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003292358,"about_ca_system_score_gemma":0.000005359653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008607419,"about_ca_topic_score_gemma":0.00000325301,"domain_scores_codex":[0.9990228,0.000009328427,0.0003470142,0.0002214676,0.0001406405,0.0002587091],"domain_scores_gemma":[0.9995595,0.0001180343,0.00001809341,0.0001626723,0.00003692161,0.0001047907],"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":[0.0001123019,0.00009102815,0.004814466,0.00205894,0.0002561748,0.000002963496,0.003714092,0.864726,0.1177411,0.0008740112,0.000291314,0.005317613],"study_design_scores_gemma":[0.0005689795,0.0003723757,0.003561036,0.0003122889,0.00004081505,0.000004963556,0.0002808346,0.9767271,0.01771249,0.00003921425,0.000187753,0.0001921813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172657,0.0002328089,0.08163454,0.0000212802,0.0003853277,0.0002117535,0.00001519573,0.0001420535,0.00009133182],"genre_scores_gemma":[0.9976175,0.0000114227,0.001942478,0.000004177944,0.0003275853,0.00001304121,0.00002068424,0.00005068424,0.00001239645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.112001,"threshold_uncertainty_score":0.8377094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04737615056259106,"score_gpt":0.2411480662141278,"score_spread":0.1937719156515367,"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."}}