{"id":"W2803312604","doi":"10.1051/matecconf/201816518005","title":"Experimental Life Improvement Quantification of Shot Peening and Fastener Modifications","year":2018,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Engineering and Material Science Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sonaca (Canada); National Research Council Canada","funders":"","keywords":"Fastener; Shot peening; Structural engineering; Computer science; Materials science; Engineering; Residual stress; Composite material","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004002203,0.00006483401,0.0001266358,0.00006836501,0.00006730595,0.00005474429,0.0001849894,0.00002901649,0.0004047136],"category_scores_gemma":[0.00005025723,0.00005161278,0.00001335708,0.00008772843,0.0003628375,0.0001077505,0.00006100625,0.00002033298,0.00001233422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006844774,"about_ca_system_score_gemma":0.0001683468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002572979,"about_ca_topic_score_gemma":0.000007647744,"domain_scores_codex":[0.99922,0.00002407465,0.0002228661,0.0001626779,0.0002262629,0.0001441431],"domain_scores_gemma":[0.99953,0.00002673896,0.00009286038,0.0001488803,0.0001393786,0.00006209844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001066668,0.00002548089,0.0001645995,0.00002789328,0.00000212194,4.212057e-8,0.000209064,0.00001160683,0.9845808,0.01456822,0.00002192744,0.0003776164],"study_design_scores_gemma":[0.00009174782,0.0001822063,0.001912871,0.00002754843,0.000002906707,4.218031e-7,0.0007545808,0.001997504,0.9946479,0.0001256131,0.0001979161,0.00005874366],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945578,0.00005791926,0.001518751,0.00009248633,0.0001632259,0.00009877906,0.00001487148,0.00002485042,0.003471313],"genre_scores_gemma":[0.9990082,0.00001067024,0.0008595528,0.000004255173,0.00003179311,0.0000178262,0.00000212074,0.000003543983,0.00006201881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01444261,"threshold_uncertainty_score":0.443133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0705605068823865,"score_gpt":0.3252167860357049,"score_spread":0.2546562791533183,"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."}}