{"id":"W1592208251","doi":"10.1007/978-3-319-48096-1_13","title":"Progressive Failure Analysis of Polymer Composites Using a Synergistic Damage Mechanics Methodology","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Micromechanics; Damage mechanics; Subroutine; Materials science; Finite element method; Ultimate tensile strength; Structural engineering; Composite material; Nonlinear system; Composite number; Computer science; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002837301,0.0006393566,0.001895183,0.001000467,0.00004759638,0.00003484525,0.0005346711,0.0007490057,0.002693351],"category_scores_gemma":[0.00003843158,0.0006109966,0.0006677416,0.0002367031,0.00007932817,0.00004351131,0.0001885634,0.0005203729,0.00002890861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000871081,"about_ca_system_score_gemma":0.00002491732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002004109,"about_ca_topic_score_gemma":0.0000297499,"domain_scores_codex":[0.9977695,0.00009541676,0.0008589248,0.000486885,0.0004163806,0.0003729196],"domain_scores_gemma":[0.997695,0.0007256353,0.0003443788,0.0008716225,0.0001841687,0.0001791626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001613656,0.00001577566,0.00000856343,0.0002174874,0.004648663,0.0000576595,0.00003344389,0.01275064,0.3668218,0.6147339,0.0001275035,0.0005683954],"study_design_scores_gemma":[0.0004481548,0.0002585838,0.00001009564,0.0005290264,0.03347966,0.00003707906,0.00001728978,0.6788892,0.2733609,0.009337288,0.001560473,0.002072234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00530448,0.001948738,0.9588979,0.00002655365,0.0003892023,0.0005305824,0.0001857686,0.0006137379,0.03210303],"genre_scores_gemma":[0.637031,0.00005339627,0.3151158,0.0001258712,0.000350938,0.00004472203,0.0008147053,0.000759759,0.0457038],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6661386,"threshold_uncertainty_score":0.9996341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04829059686354661,"score_gpt":0.2829972823782481,"score_spread":0.2347066855147015,"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."}}