{"id":"W4288026092","doi":"10.48550/arxiv.1911.05225","title":"Optimal load sharing in bioinspired fibrillar adhesives: Asymptotic\\n solution","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Adhesion, Friction, and Surface Interactions","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adhesive; Materials science; Fibril; Load distribution; Sensitivity (control systems); Load sharing; Load bearing; Mechanics; Composite material; Biological system; Computer science; Structural engineering; Physics; Biophysics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006486835,0.0005149397,0.0006278369,0.0006783886,0.0004475054,0.0009132204,0.0008731447,0.001903662,0.001577877],"category_scores_gemma":[0.003402938,0.0004081859,0.0004700925,0.0003030583,0.001310463,0.001229947,0.001264578,0.0007853826,0.0002549367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009607872,"about_ca_system_score_gemma":0.0007814953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001741128,"about_ca_topic_score_gemma":0.001515242,"domain_scores_codex":[0.9997543,0.00005656918,0.000009502487,0.00005879314,0.0000808617,0.00004010174],"domain_scores_gemma":[0.9993819,0.0003127239,0.000118327,0.0000418049,0.00009823557,0.00004700081],"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":[0.00004146804,0.0001074191,0.0007712112,0.0001555181,0.00001762168,0.0002626234,0.0001165338,0.7701225,0.0123695,0.2016169,0.001437387,0.01298129],"study_design_scores_gemma":[0.000005741049,0.00001631489,0.0001117918,0.0000111539,0.000001968743,0.00003709075,0.00002478267,0.9733495,0.000574338,0.02526717,0.0005940989,0.000006179109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09686686,0.0008784342,0.8810238,0.0008127423,0.00008397571,0.00004824836,0.00006600123,0.0002135839,0.02000649],"genre_scores_gemma":[0.8856255,0.0008820947,0.09921457,0.0003734789,0.0001120524,0.0002122518,0.00009905828,0.000115201,0.01336591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001903662,"threshold_uncertainty_score":0.006971002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441357888145956,"score_gpt":0.1829961807767564,"score_spread":0.1388603919621608,"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."}}