{"id":"W2029888910","doi":"10.4028/www.scientific.net/amm.612.145","title":"Selection of Material for Wind Turbine Blade by Analytic Hierarchy Process (AHP) Method","year":2014,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Material selection; Wind power; Turbine blade; Analytic hierarchy process; Turbine; Blade (archaeology); Renewable energy; Engineering; Electricity generation; Marine engineering; Reliability engineering; Structural engineering; Mechanical engineering; Power (physics); Materials science; Operations research","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002414313,0.0009955425,0.001114966,0.001688591,0.001025707,0.00121648,0.0009919754,0.0007678929,0.003399661],"category_scores_gemma":[0.00324027,0.0004401628,0.00112254,0.001505143,0.0005803577,0.0006951487,0.0008385361,0.0009021694,0.0004780495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006720591,"about_ca_system_score_gemma":0.002089856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003096729,"about_ca_topic_score_gemma":0.003039151,"domain_scores_codex":[0.9979717,0.0007115214,0.0001611839,0.0001979528,0.0008181505,0.0001394769],"domain_scores_gemma":[0.9983329,0.001002362,0.000160842,0.00003957456,0.0004235574,0.00004077768],"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":[0.0002853613,0.0003027682,0.001944927,0.001978392,0.0001552811,0.0003700083,0.0008241382,0.6149971,0.02959193,0.01260287,0.003293787,0.3336534],"study_design_scores_gemma":[0.00006669671,0.0002177052,0.0005153585,0.00007724854,0.00005707631,0.00005854664,0.0002514032,0.9790796,0.007120207,0.009166108,0.003358029,0.00003204963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01055652,0.0001534077,0.9869086,0.00007740374,0.00002427456,0.0003649446,0.0001281539,0.0002357917,0.001550913],"genre_scores_gemma":[0.1988658,0.0002653788,0.7987793,0.00004880991,0.00002742328,0.0007212515,0.0003431834,0.00004955562,0.0008993893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003399661,"threshold_uncertainty_score":0.01276827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006040795610481997,"score_gpt":0.2282571689384566,"score_spread":0.2222163733279746,"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."}}