{"id":"W2285152100","doi":"10.1007/978-1-4614-4226-4_29","title":"Application of a New Experimental Method to Determine Bi-Material Interface Bonding Strength","year":2012,"lang":"en","type":"book-chapter","venue":"Conference proceedings of the Society for Experimental Mechanics","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Materials science; Composite material; Ultimate tensile strength; Discontinuity (linguistics); Interface (matter); Envelope (radar); Epoxy; Stiffness; Structural engineering; Finite element method; Stress (linguistics); Singularity; Strength of materials; Bonding strength; Material properties; Shear strength (soil); Viscoelasticity; Shear (geology); Computer science; Engineering; Mathematics; Geometry; Mathematical analysis","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":[0.0002191793,0.0005883423,0.0007771273,0.0000688548,0.00008184479,0.00005575118,0.0009826575,0.0004618652,0.0001686748],"category_scores_gemma":[0.0000126701,0.0005473814,0.0009293474,0.00007508132,0.00004504732,0.000195001,0.0005669025,0.0002769236,0.000006282547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003048412,"about_ca_system_score_gemma":0.0000414557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007585001,"about_ca_topic_score_gemma":2.707369e-7,"domain_scores_codex":[0.9979595,0.000002917033,0.0007511405,0.0004426838,0.0004421081,0.0004016403],"domain_scores_gemma":[0.9987881,0.00004505428,0.0004544573,0.0002947735,0.0001875247,0.0002301],"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":[0.00005600112,0.00005077433,5.22859e-7,0.000206698,0.0001393299,1.634824e-8,0.001845313,0.000005828029,0.8915913,0.1029087,0.0008416787,0.002353817],"study_design_scores_gemma":[0.0004055557,0.0003392084,1.910847e-7,0.000389757,0.0002004969,0.000004942988,0.000873967,0.006136843,0.9832747,0.003067558,0.004816075,0.0004907027],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3126878,0.01242327,0.619615,0.0004383148,0.008118589,0.02295223,0.002208449,0.002004254,0.0195521],"genre_scores_gemma":[0.9005702,0.00002021612,0.09518531,0.00002657305,0.0002381911,0.00024132,0.00002306216,0.0001970457,0.003498092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5878824,"threshold_uncertainty_score":0.9996977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03468534835854011,"score_gpt":0.2949548167282122,"score_spread":0.2602694683696721,"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."}}