{"id":"W1992298341","doi":"10.1016/j.ijfatigue.2014.03.022","title":"Extraction of stress intensity factors for 3D small fatigue cracks using digital volume correlation and X-ray tomography","year":2014,"lang":"en","type":"article","venue":"International Journal of Fatigue","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Stress intensity factor; Materials science; Intensity (physics); Tomography; Amplitude; X-ray; Stress concentration; Fatigue testing; Stress (linguistics); Structural engineering; Composite material; Fracture mechanics; Optics; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001722877,0.000143578,0.0002317653,0.0002877821,0.0000321672,0.00007437735,0.0001618458,0.0001029222,0.00001101868],"category_scores_gemma":[0.0002386189,0.00013177,0.0001340708,0.0000735838,0.00003188448,0.0005348208,0.00001834538,0.0001983019,3.019091e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005473365,"about_ca_system_score_gemma":0.00001529067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001660626,"about_ca_topic_score_gemma":0.000006361239,"domain_scores_codex":[0.9990201,0.00001533739,0.0004871619,0.0000955352,0.0002678701,0.0001139943],"domain_scores_gemma":[0.9986771,0.0001988145,0.0003537749,0.00007785607,0.0006236563,0.00006879856],"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":[0.0004737082,0.0003214545,0.2291802,0.0003052783,0.001497961,0.00001863377,0.003567528,0.6018295,0.04200656,0.001215508,0.0007001798,0.1188835],"study_design_scores_gemma":[0.001273862,0.0003183228,0.04885287,0.0005268646,0.0001274802,0.00006716165,0.0006664127,0.9328764,0.01174944,0.001360645,0.001814909,0.0003656236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4785254,0.00005497651,0.5200753,0.00002316906,0.001159209,0.00005486079,0.00003528388,0.00001195727,0.00005986973],"genre_scores_gemma":[0.9907466,0.00002144257,0.008913452,0.00001335932,0.0002397475,9.497558e-7,0.00003506879,0.00002041607,0.000009004349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5122212,"threshold_uncertainty_score":0.5373424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02804122399468454,"score_gpt":0.2594380922215982,"score_spread":0.2313968682269137,"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."}}