{"id":"W4321460131","doi":"10.1016/j.cmpb.2023.107420","title":"Modeling fibrous soft tissue dissection with elastic-plastic deformation for simulation of brain tumor removal","year":2023,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"China Postdoctoral Science Foundation; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Soft tissue; Dissection (medical); Deformation (meteorology); Materials science; Brain tissue; Computer science; Biomedical engineering; Composite material; Anatomy; Surgery; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0005305031,0.000117227,0.0002176329,0.0002134439,0.00003923143,0.00002147565,0.00004289183,0.00005440109,8.343968e-7],"category_scores_gemma":[0.00006072014,0.00009485551,0.0000146845,0.0003492887,0.00003232944,0.0001051046,0.00002065278,0.00006272391,4.468594e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001821418,"about_ca_system_score_gemma":0.0000062711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001299281,"about_ca_topic_score_gemma":0.000006871376,"domain_scores_codex":[0.9992574,0.00003717844,0.0003031921,0.0001377993,0.00008549709,0.0001789629],"domain_scores_gemma":[0.9993953,0.0004069254,0.0000343414,0.00007100961,0.00004985574,0.00004255641],"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":[0.00005596335,0.000008249662,0.00001532994,0.0004650316,0.000009660697,0.000002214494,0.0003840952,0.7308854,0.005951555,0.00003569641,0.000001978745,0.2621848],"study_design_scores_gemma":[0.000721156,0.0004892622,0.00006881338,0.0004188218,0.00001970743,0.00002137148,0.00005574102,0.9966432,0.0006091303,0.0006685416,0.0001771046,0.0001071329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3649326,0.00004531281,0.6343173,0.000017119,0.0003387915,0.0002213192,0.000001989863,0.0001235141,0.000002003971],"genre_scores_gemma":[0.6873975,0.000006205181,0.3123551,0.000006379624,0.0001449386,0.00002239591,0.00004987679,0.00001596903,0.000001540465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3224649,"threshold_uncertainty_score":0.3868095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03969087293131704,"score_gpt":0.3264154225783828,"score_spread":0.2867245496470657,"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."}}