{"id":"W4353092347","doi":"10.3390/applmech4010021","title":"Combining Digital Image Correlation and Acoustic Emission to Characterize the Flexural Behavior of Flax Biocomposites","year":2023,"lang":"en","type":"article","venue":"Applied Mechanics","topic":"Natural Fiber Reinforced Composites","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital image correlation; Acoustic emission; Materials science; Stacking; Flexural strength; Breakage; Cluster analysis; Isotropy; Structural engineering; Composite material; Computer science; Artificial intelligence; Engineering; Optics","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":[0.0004733733,0.0003882704,0.0002199876,0.001499128,0.0001157747,0.0002796998,0.0002107657,0.0002659251,0.0005840556],"category_scores_gemma":[0.000762642,0.0001655689,0.0001321868,0.0007459163,0.0003409251,0.000495327,0.0003398711,0.0002557834,0.0001246308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001997874,"about_ca_system_score_gemma":0.0002096315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00079754,"about_ca_topic_score_gemma":0.002139885,"domain_scores_codex":[0.9997451,0.00003434316,0.00001441313,0.00006103059,0.0001140153,0.00003110047],"domain_scores_gemma":[0.9994677,0.0002020451,0.00009480409,0.00005391738,0.0001592972,0.00002224828],"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":[0.0001777868,0.00006253712,0.003822785,0.0001179028,0.00002223035,0.00007301039,0.00008443119,0.002984714,0.9208429,0.0002385063,0.0001106832,0.07146241],"study_design_scores_gemma":[0.00001207966,0.0002274355,0.03320477,0.00001452794,0.00005214321,0.0004729809,0.0001455952,0.08919925,0.8751422,0.0002491054,0.001239312,0.00004052747],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8318806,0.0006839975,0.1642329,0.00007647331,0.00002918499,0.00007900053,0.0002035034,0.0003906452,0.002423784],"genre_scores_gemma":[0.8624941,0.0004689835,0.1353115,0.00005277546,0.00002359182,0.00006386361,0.0001968074,0.00003146043,0.001356939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001499128,"threshold_uncertainty_score":0.002503514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01277044211685939,"score_gpt":0.2386348340493468,"score_spread":0.2258643919324874,"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."}}