{"id":"W3038389658","doi":"10.1016/j.coco.2020.100384","title":"Crack characterization of discontinuous fiber-reinforced composites by using micro-computed tomography: Cyclic in-situ testing, crack segmentation and crack volume fraction","year":2020,"lang":"en","type":"article","venue":"Composites Communications","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Deutsche Forschungsgemeinschaft","keywords":"Materials science; Composite material; Thermosetting polymer; Volume fraction; Characterization (materials science); Stiffness; Fracture toughness; Fiber; Microstructure; Fracture mechanics; Fracture (geology); Toughness","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001159864,0.0002958413,0.0003980594,0.0002435341,0.0002165011,0.0001225678,0.0005565141,0.0001201026,0.00001050298],"category_scores_gemma":[0.00007405256,0.0003695149,0.00006265038,0.0008905014,0.0002134627,0.0006341147,0.0002862459,0.000376247,0.000007417966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001115736,"about_ca_system_score_gemma":0.0000182548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001098414,"about_ca_topic_score_gemma":0.00001054588,"domain_scores_codex":[0.9984872,0.000148371,0.0006880355,0.0002780919,0.0001527896,0.0002455491],"domain_scores_gemma":[0.9983326,0.0003615688,0.0003378054,0.0006857713,0.0001754405,0.0001068158],"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":[0.00001157189,0.00004841943,0.05427061,0.0001060968,0.00004006537,5.983674e-7,0.0003890603,0.0006562684,0.9433171,0.00005965954,0.00006329802,0.001037217],"study_design_scores_gemma":[0.0008864728,0.0001940418,0.2025922,0.0005564859,0.0001342364,0.0000287906,0.00008358307,0.30676,0.4873191,0.000475249,0.0002004246,0.0007693614],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574078,0.0003474696,0.03985658,0.000252322,0.00003385302,0.0006340463,0.00007425288,0.0006956708,0.0006979796],"genre_scores_gemma":[0.6982593,0.00005001453,0.3008903,0.00005495278,0.00001917487,0.00002734731,0.0006480616,0.000046825,0.000004003093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.455998,"threshold_uncertainty_score":0.9998757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02503245956597305,"score_gpt":0.2517814587679283,"score_spread":0.2267489992019552,"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."}}