{"id":"W1615789517","doi":"10.1111/ffe.12293","title":"Numerical investigation of compliance equations used in the R‐curve testing for clamped SE(T) specimens","year":2015,"lang":"en","type":"article","venue":"Fatigue & Fracture of Engineering Materials & Structures","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Tension (geology); Materials science; Crack tip opening displacement; Structural engineering; Single specimen; Displacement (psychology); Enhanced Data Rates for GSM Evolution; Range (aeronautics); Plane (geometry); Ranging; Compliance (psychology); Composite material; Mechanics; Geometry; Mathematics; Engineering; Physics; Stress intensity factor; Geology; Ultimate tensile strength","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001269887,0.0002260707,0.0002444669,0.0004919452,0.0002810358,0.0003802151,0.0007422698,0.0007028305,0.001055855],"category_scores_gemma":[0.003702903,0.0002757233,0.000336619,0.0002915793,0.0005131261,0.0004224872,0.000270555,0.0003315273,0.0001831882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003401636,"about_ca_system_score_gemma":0.0006695479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005307063,"about_ca_topic_score_gemma":0.006703933,"domain_scores_codex":[0.9995815,0.00008094957,0.00004140311,0.0000542685,0.0002133901,0.00002853287],"domain_scores_gemma":[0.9982205,0.000998735,0.0002340489,0.0001931573,0.0003243086,0.00002925359],"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":[0.0002069178,0.0002237279,0.01774888,0.0002784219,0.00003970909,0.0006809174,0.000761417,0.5952719,0.3233016,0.006723189,0.0004374798,0.05432579],"study_design_scores_gemma":[0.00001110208,0.00006025779,0.001896212,0.00001615185,0.000005082042,0.00007004967,0.00005274149,0.9761432,0.02136506,0.0001339409,0.0002335038,0.00001257639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7903977,0.0001045935,0.2061715,0.00008118984,0.00001477555,0.0001202138,0.00009491376,0.0003646465,0.002650409],"genre_scores_gemma":[0.9591323,0.00003396612,0.04015656,0.000009239575,0.00000123791,0.00005052801,0.00002835567,0.00002134243,0.0005665983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005307063,"threshold_uncertainty_score":0.01055229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1090268277397292,"score_gpt":0.2887610515721918,"score_spread":0.1797342238324626,"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."}}