{"id":"W4256284818","doi":"10.32920/ryerson.14646690.v1","title":"Compressive Mesoscale Damage Modeling of Continuous Fiber-Reinforced Flax Laminates","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Natural Fiber Reinforced Composites","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Epoxy; Materials science; Composite material; Composite laminates; Tension (geology); Glass fiber; Fiber; Compression (physics); Composite number; Compressive strength; Plasticity; Fibre-reinforced plastic; Damage mechanics; Structural engineering; Finite element method; Engineering","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":[0.000165724,0.000325179,0.000216472,0.0003302044,0.000183584,0.0003671278,0.0004657923,0.0006799949,0.0009418408],"category_scores_gemma":[0.0003195151,0.000151153,0.0002991819,0.0001534408,0.0004090994,0.000334795,0.0003026504,0.0003277286,0.000115768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005562786,"about_ca_system_score_gemma":0.0003219785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00460276,"about_ca_topic_score_gemma":0.004291807,"domain_scores_codex":[0.9999459,0.000007568178,0.000002985431,0.00001309768,0.00001954088,0.00001094942],"domain_scores_gemma":[0.9998704,0.00004754996,0.00002811399,0.00001636233,0.00002420358,0.00001328369],"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":[0.0000153621,0.00002263324,0.0007353152,0.00001287759,0.000003797339,0.00004216156,0.00001584196,0.9908862,0.005759582,0.0007163604,0.00005378339,0.001736102],"study_design_scores_gemma":[0.000001029473,0.000007884883,0.0004410554,0.000001365598,7.345983e-7,0.000006211798,0.000003576923,0.9988938,0.000492115,0.000100055,0.0000509631,0.000001187761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9106586,0.0003907109,0.07844331,0.0001356551,0.00002190847,0.00006097951,0.0002915274,0.000219679,0.009777587],"genre_scores_gemma":[0.9945228,0.00009344181,0.003554522,0.000009161608,0.000003765216,0.00002140023,0.00004958229,0.0000142447,0.001731017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00460276,"threshold_uncertainty_score":0.009151936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543825873674758,"score_gpt":0.2521140455533786,"score_spread":0.236675786816631,"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."}}