{"id":"W3109077102","doi":"10.1016/b978-0-12-818984-9.00016-0","title":"Modelling damage evolution in multidirectional laminates: micro to macro","year":2020,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microscale chemistry; Materials science; Macro; Composite laminates; Stiffness; Cracking; Context (archaeology); Structural engineering; Fibre-reinforced plastic; Composite material; Composite number; Computer science; Engineering; Geology","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":[0.0001134472,0.0004425721,0.000489249,0.0002611752,0.00004210016,0.00003863265,0.00028549,0.0003407219,0.0001289231],"category_scores_gemma":[0.00000886525,0.000524502,0.0001658614,0.00003250768,0.00002352264,0.00004453028,0.0001121047,0.0007262223,0.0005260546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003853317,"about_ca_system_score_gemma":0.00002960438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001599552,"about_ca_topic_score_gemma":0.00001759578,"domain_scores_codex":[0.9984453,0.00001593886,0.0004986039,0.0004472936,0.000289143,0.0003037085],"domain_scores_gemma":[0.9993105,0.00006258454,0.00005164023,0.0003223066,0.0000542905,0.0001986918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008734192,0.00003515345,0.0000260352,0.0007087964,0.0001897447,0.0003133796,0.0006832986,0.1637648,0.0913813,0.02012018,0.0003869415,0.722303],"study_design_scores_gemma":[0.0007900642,0.0001388712,0.000081164,0.002136099,0.0001883812,0.00002541813,0.00001076762,0.181829,0.01027665,0.01385543,0.7883442,0.002323912],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002616295,0.0007643293,0.005479475,0.00004474555,0.0006722274,0.000841247,0.00008726409,0.0005564005,0.988938],"genre_scores_gemma":[0.09795898,0.00006180437,0.02245628,0.0001699717,0.0005621546,0.0001503359,0.00009548568,0.0004520747,0.8780929],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7879573,"threshold_uncertainty_score":0.9997206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167407048847508,"score_gpt":0.2206419631095906,"score_spread":0.2039012582248398,"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."}}