{"id":"W2017748463","doi":"10.1115/ipc2006-10330","title":"Local Stress-Strain Response of an Axial X100 Girth Weld Under Tensile Loading Using Digital Image Correlation","year":2006,"lang":"en","type":"article","venue":"Volume 3: Materials and Joining; Pipeline Automation and Measurement; Risk and Reliability, Parts A and B","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Girth (graph theory); Digital image correlation; Welding; Materials science; Ultimate tensile strength; Structural engineering; Strain (injury); Stress (linguistics); Tensile testing; Composite material; Mathematics; Engineering","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":[0.000396681,0.0003335763,0.0002154951,0.0007945271,0.0001800254,0.0001910365,0.0003642642,0.0003882802,0.002268367],"category_scores_gemma":[0.0005255453,0.0002402586,0.0001498693,0.0007078666,0.0003305467,0.0002524242,0.0002481227,0.0002322934,0.0002594139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000221245,"about_ca_system_score_gemma":0.0001236563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0017736,"about_ca_topic_score_gemma":0.004362817,"domain_scores_codex":[0.9997342,0.00001676616,0.00001787951,0.00005885546,0.0001438796,0.00002847441],"domain_scores_gemma":[0.9993858,0.0001737405,0.000109272,0.00006112362,0.0002044911,0.00006554587],"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":[0.0001993819,0.00005214011,0.002396521,0.00006086317,0.00001014036,0.000160838,0.0001597986,0.00111804,0.9870913,0.00004506339,0.0000764628,0.00862952],"study_design_scores_gemma":[0.00001249957,0.001130957,0.1589555,0.00002216976,0.00003585864,0.0005282747,0.000272321,0.0252888,0.8129769,0.00005333737,0.0006767209,0.00004672221],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929039,0.00018778,0.00548385,0.00001900309,0.00001003118,0.00001771255,0.0001550862,0.0001575006,0.001065106],"genre_scores_gemma":[0.9943923,0.0001188212,0.004301044,0.00002221454,0.000004898104,0.00001319867,0.0001271473,0.00001634382,0.001004004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002268367,"threshold_uncertainty_score":0.007588446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01540008460587337,"score_gpt":0.2307047348417037,"score_spread":0.2153046502358303,"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."}}