{"id":"W4409903119","doi":"10.1016/j.compositesb.2025.112575","title":"Effects of impactor geometry and multiple impacts on low-velocity impact response and residual compressive strength of fiber-reinforced composite laminates","year":2025,"lang":"en","type":"article","venue":"Composites Part B Engineering","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale; Canadian Armed Forces","keywords":"Materials science; Composite material; Compressive strength; Residual strength; Composite number; Residual; Composite laminates; Fiber; Izod impact strength test; Ultimate tensile strength","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":[0.0002734517,0.0006333789,0.000335433,0.0004419075,0.0002674823,0.0003002214,0.0002925575,0.0003598358,0.001415116],"category_scores_gemma":[0.0005764634,0.0002783397,0.0003161091,0.0002012316,0.000385285,0.0003518357,0.0004022364,0.0003207958,0.0001587453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002510929,"about_ca_system_score_gemma":0.0001637578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001617802,"about_ca_topic_score_gemma":0.002258543,"domain_scores_codex":[0.9997612,0.00001937342,0.00001123542,0.00005152732,0.00007282348,0.00008386641],"domain_scores_gemma":[0.9994916,0.0002132616,0.0001088325,0.00004276653,0.00007949937,0.00006414447],"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":[0.001330838,0.0002747609,0.03019896,0.0001400088,0.00005048422,0.00107481,0.0002367192,0.04776913,0.9037839,0.00009350768,0.00009435284,0.01495256],"study_design_scores_gemma":[0.00002964893,0.002390839,0.2666336,0.00002196136,0.00008997333,0.0005001506,0.00055143,0.08297834,0.646267,0.00007467614,0.0003997246,0.00006268996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992489,0.00004011462,0.0004937369,0.000002850781,0.000002038613,0.00000473787,0.00001977006,0.00001639113,0.000171372],"genre_scores_gemma":[0.9996525,0.00002837336,0.0001575785,0.000003270078,5.972237e-7,0.000002360546,0.00002137324,0.000004056197,0.0001298432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001617802,"threshold_uncertainty_score":0.00473398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00495552822419839,"score_gpt":0.2294771485931071,"score_spread":0.2245216203689087,"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."}}