{"id":"W2542483411","doi":"10.1109/tic-sth.2009.5444518","title":"Nonlinear finite element-based modeling of soft-tissue cutting","year":2009,"lang":"en","type":"article","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Colleges and Universities","keywords":"Finite element method; Discretization; Nonlinear system; Computer science; Deformation (meteorology); Compressibility; Structural engineering; Engineering; Mathematics; Mathematical analysis; Materials science","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":[0.0002929111,0.0004098301,0.0004157323,0.0003590314,0.0002602318,0.0005483057,0.001135789,0.001032909,0.00208468],"category_scores_gemma":[0.0007860168,0.000306722,0.0005211969,0.0002778728,0.0005273721,0.0006266503,0.0005810315,0.0005083423,0.0006788882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004086148,"about_ca_system_score_gemma":0.0005769914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002576603,"about_ca_topic_score_gemma":0.002168016,"domain_scores_codex":[0.9998393,0.00004126193,0.00001061701,0.00002032564,0.00007830505,0.0000101324],"domain_scores_gemma":[0.9997839,0.0001140964,0.00002649982,0.00002541458,0.0000395345,0.00001059435],"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":[0.00001792772,0.00001970594,0.0002794188,0.00005948257,0.00000747869,0.00007954313,0.0000719208,0.9698516,0.009976586,0.01015019,0.0001688864,0.009317226],"study_design_scores_gemma":[0.000001714957,0.000006115734,0.00005266121,0.000003589753,0.000001523567,0.00002307249,0.000004845905,0.997062,0.0009659547,0.0008199945,0.001055251,0.00000331639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02118289,0.0002514176,0.9716068,0.0001284199,0.00003885224,0.00005023458,0.0001114711,0.000210648,0.006419375],"genre_scores_gemma":[0.5579506,0.001130766,0.4216477,0.0001151006,0.00003083985,0.0003525317,0.0003496675,0.0001520618,0.01827065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002576603,"threshold_uncertainty_score":0.006973922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554497045590916,"score_gpt":0.2472525905318488,"score_spread":0.2317076200759396,"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."}}