{"id":"W2044282185","doi":"10.1115/gt2010-22169","title":"Probabilistic Creep Life Prediction of Turbine Discs","year":2010,"lang":"en","type":"article","venue":"","topic":"High Temperature Alloys and Creep","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Life Prediction Technologies (Canada)","funders":"","keywords":"Creep; Probabilistic logic; Turbine; Probabilistic analysis of algorithms; Reliability (semiconductor); Computer science; Materials science; Structural engineering; Reliability engineering; Mechanical engineering; Engineering; Composite material; Physics","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":[0.001092781,0.0003192383,0.000316605,0.0006943445,0.0002023558,0.0002741947,0.000479761,0.0006243367,0.0003826106],"category_scores_gemma":[0.004926861,0.0002128214,0.0004284502,0.0003311545,0.0003412721,0.0005408474,0.0002275526,0.000265436,0.00009445712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005991126,"about_ca_system_score_gemma":0.0002420347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002327528,"about_ca_topic_score_gemma":0.001804199,"domain_scores_codex":[0.9996777,0.00007145109,0.00002194476,0.00006058437,0.0001326515,0.00003573885],"domain_scores_gemma":[0.9973378,0.001449366,0.0003982177,0.0002676433,0.0005030849,0.00004400382],"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":[0.00008956349,0.00001731157,0.01686798,0.00001672101,0.00001340181,0.0001155441,0.00003682534,0.9687117,0.005124327,0.0005317687,0.0001293762,0.008345656],"study_design_scores_gemma":[0.000003148692,0.00009199888,0.0101193,0.000002805758,0.000004837971,0.00008647442,0.000008646522,0.9847439,0.004227586,0.0005931937,0.0001074395,0.00001072145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.96937,0.0001446802,0.02930509,0.00006090856,0.000004102376,0.00001030584,0.0001456688,0.0001315523,0.0008276485],"genre_scores_gemma":[0.9988475,0.00001542552,0.0009984364,0.00000195774,0.000001027755,0.000004024859,0.00005897253,0.000004107351,0.00006863334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002327528,"threshold_uncertainty_score":0.005779207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004472072550205593,"score_gpt":0.1730554623280002,"score_spread":0.1685833897777946,"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."}}