{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004431788,0.0008546595,0.0005975218,0.003431837,0.0002587094,0.0008981485,0.0005112223,0.0009775599,0.001271134],"category_scores_gemma":[0.001863444,0.0006312314,0.0006222563,0.001689562,0.0002748744,0.0009910195,0.0004884872,0.0004168931,0.0006102741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002481669,"about_ca_system_score_gemma":0.0008285267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001763687,"about_ca_topic_score_gemma":0.003914697,"domain_scores_codex":[0.9997569,0.00002210214,0.00002326871,0.00005367913,0.0001091835,0.00003489352],"domain_scores_gemma":[0.9987931,0.0004457514,0.0001806627,0.00008284106,0.0004541735,0.00004347113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005101566,0.0001760556,0.02931411,0.0005594588,0.00008989924,0.0004766099,0.0004377445,0.03045127,0.4853264,0.001561527,0.001693236,0.4494035],"study_design_scores_gemma":[0.00005710933,0.0002386697,0.0963612,0.00007813198,0.0001742701,0.001193144,0.000312582,0.7575463,0.1381225,0.001631428,0.004135963,0.0001487527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3049425,0.0007595257,0.6898586,0.00006600528,0.00002967158,0.000161245,0.0006821586,0.00232583,0.001174423],"genre_scores_gemma":[0.6657661,0.0004008111,0.3320166,0.00002847634,0.00002782746,0.0001005914,0.0007685212,0.0002600744,0.0006310485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003431837,"threshold_uncertainty_score":0.004252374,"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."}}