{"id":"W4322487270","doi":"10.20944/preprints202302.0472.v1","title":"Combining Digital Image Correlation and Acoustic Emission to Characterize the Flexural Behavior of Flax Biocomposites","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Natural Fiber Reinforced Composites","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Digital image correlation; Acoustic emission; Stacking; Materials science; Flexural strength; Isotropy; Cluster analysis; Breakage; Structural engineering; Mechanism (biology); Sequence (biology); Computer science; Composite material; Artificial intelligence; Engineering; Optics; 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":[0.0005374615,0.0004286922,0.0002324983,0.001800054,0.0001216911,0.0003319622,0.0002210945,0.0003117946,0.0005960484],"category_scores_gemma":[0.0008503421,0.0001757965,0.0001547502,0.0009031666,0.0003602489,0.0005472338,0.0003863635,0.0002807522,0.0001487738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002135399,"about_ca_system_score_gemma":0.0002171674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008078226,"about_ca_topic_score_gemma":0.001872063,"domain_scores_codex":[0.9997064,0.00003911062,0.00001640326,0.0000767341,0.0001253651,0.00003586809],"domain_scores_gemma":[0.9994082,0.0002215586,0.0001019118,0.00007097794,0.000172525,0.00002487396],"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":[0.0001996616,0.00007555458,0.003953049,0.0001263065,0.00002443447,0.00008197573,0.00010006,0.00357996,0.9164892,0.0002903007,0.0001224413,0.0749571],"study_design_scores_gemma":[0.00001238857,0.0002096487,0.03186769,0.00001397797,0.00004986726,0.0004117091,0.0001386973,0.09210327,0.8736576,0.0002897907,0.001204464,0.00004087478],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8158379,0.000662268,0.179886,0.00007775118,0.00003487204,0.0000921644,0.0002681453,0.0004711619,0.002669741],"genre_scores_gemma":[0.8471141,0.0005073134,0.1503461,0.00005137192,0.00002872666,0.00007255057,0.000265218,0.00004075117,0.001573795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001800054,"threshold_uncertainty_score":0.002842367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07056846685164914,"score_gpt":0.32221663965243,"score_spread":0.2516481728007809,"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."}}