{"id":"W2129475333","doi":"10.1243/03093247jsa448","title":"The use of digital image correlation in a parametric study on the effect of edge distance and thickness on residual strains after hole cold expansion","year":2008,"lang":"en","type":"article","venue":"The Journal of Strain Analysis for Engineering Design","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Ministère de la Défense Nationale","keywords":"Fastener; Digital image correlation; Interference fit; Enhanced Data Rates for GSM Evolution; Materials science; Residual; Composite material; Structural engineering; Mathematics; Engineering; Telecommunications; Metallurgy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001299366,0.0001522633,0.0003231827,0.0002860622,0.00005372112,0.00003195759,0.0001597757,0.00004730794,8.183637e-7],"category_scores_gemma":[0.0004339954,0.00007685582,0.0001278327,0.0006868661,0.00004412203,0.0001371942,0.000008733104,0.0002807336,1.505422e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003426017,"about_ca_system_score_gemma":0.000009832095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002213289,"about_ca_topic_score_gemma":0.000003392679,"domain_scores_codex":[0.9989616,0.0001193123,0.0004203819,0.0000711435,0.0002890218,0.0001384928],"domain_scores_gemma":[0.9965445,0.002994233,0.0001613471,0.0002152291,0.00005583182,0.00002886162],"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":[0.0002875312,0.00003932885,0.0007517797,0.00002490617,0.0003960622,0.000007449119,0.0009413235,0.9936132,0.003385352,0.00004993417,0.00002729114,0.0004758161],"study_design_scores_gemma":[0.001467214,0.002875456,0.05183201,0.0002132166,0.001039634,0.00001176121,0.0005930377,0.9277438,0.01388537,0.00005515747,0.00003473929,0.000248617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6241884,0.0001331946,0.3753283,0.00001783437,0.00003777329,0.0002704069,0.00001702071,0.000005693054,0.000001392841],"genre_scores_gemma":[0.9995237,0.00006276491,0.0003555203,0.000002644134,0.00002079532,0.00001041599,0.000001231547,0.00001805334,0.000004864426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3753353,"threshold_uncertainty_score":0.3134089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820489226078797,"score_gpt":0.2242061128620592,"score_spread":0.1960012206012712,"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."}}