{"id":"W2992772646","doi":"","title":"Evaluation of stress intensity factor for turbine blade using finite element method","year":2018,"lang":"en","type":"article","venue":"International journal of advance research, ideas and innovations in technology","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Fillet (mechanics); Structural engineering; Turbine blade; Stress intensity factor; von Mises yield criterion; Stress concentration; Finite element method; Centrifugal compressor; Stress (linguistics); Gas compressor; Materials science; Engineering; Turbine; Mechanical 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":[0.001817593,0.00007198114,0.0001666279,0.001423815,0.00003691959,0.0000136675,0.0002418191,0.00009100759,0.00002121132],"category_scores_gemma":[0.002290732,0.00006720295,0.00002471997,0.0006567811,0.0001140658,0.0002053639,0.00006137228,0.00032904,2.757425e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002305153,"about_ca_system_score_gemma":0.00008554575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007723203,"about_ca_topic_score_gemma":0.00003619244,"domain_scores_codex":[0.9986535,0.00003965643,0.0004897526,0.00009288757,0.0005720829,0.0001521627],"domain_scores_gemma":[0.9915268,0.0001497887,0.0001614787,0.000103094,0.008040643,0.00001822835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001754772,0.0001607152,0.002145419,0.00006543845,0.0004060674,0.000008005724,0.0004760272,0.04219062,0.1295426,0.04670546,0.0001839935,0.7779402],"study_design_scores_gemma":[0.001401379,0.0004015126,0.001379273,0.0003111344,0.00002480935,0.00004087872,0.0006283949,0.5535842,0.2426948,0.1960864,0.003321694,0.0001254636],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4450839,0.0004938701,0.552862,0.0007788226,0.000476511,0.0001906779,0.0000445576,0.00001218763,0.00005743724],"genre_scores_gemma":[0.9205314,0.000174058,0.0791316,0.00001833755,0.0001207644,0.000007875867,0.000003762208,0.0000096928,0.000002521899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7778147,"threshold_uncertainty_score":0.2742386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09080198778564336,"score_gpt":0.441091550400612,"score_spread":0.3502895626149686,"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."}}