{"id":"W4411986713","doi":"10.1088/1361-6560/adebd8","title":"Patient-specific virtual surgical planning for tongue reconstruction: evaluating hyperelastic inverse FEM with four simulated tongue cancer cases","year":2025,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Reconstructive Surgery and Microvascular Techniques","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Misericordia Community Hospital; University of Alberta Hospital; University of Alberta","funders":"Alberta Cancer Foundation","keywords":"Hyperelastic material; Tongue; Finite element method; Cancer; Computer science; Medicine; Inverse; Surgical planning; Orthodontics; Radiology; Mathematics; Pathology; Geometry; Structural engineering; Engineering; Internal medicine","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":[0.0006283596,0.0005788791,0.0003100383,0.0004494435,0.0002447589,0.0005482694,0.00056654,0.0009778356,0.001619081],"category_scores_gemma":[0.001935738,0.0003665772,0.0006722228,0.000216328,0.0005056698,0.0002154394,0.0004964581,0.0003390737,0.000178836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005802946,"about_ca_system_score_gemma":0.0005294048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003212593,"about_ca_topic_score_gemma":0.003902695,"domain_scores_codex":[0.9997576,0.00007032676,0.00001753792,0.00003740077,0.00009094503,0.00002627894],"domain_scores_gemma":[0.9992374,0.0005373199,0.00005667463,0.00006901404,0.00007024541,0.00002922762],"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":[0.0002345235,0.0001372356,0.003587772,0.0001037466,0.00003137341,0.0003739175,0.0001249711,0.9745675,0.006756891,0.0004726889,0.0002805546,0.01332888],"study_design_scores_gemma":[0.00003419838,0.0002970942,0.001648355,0.00001447551,0.00001696278,0.0002789832,0.0001448032,0.9910137,0.005682016,0.0002840798,0.0005679707,0.00001724796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637665,0.0001379205,0.03273627,0.00009901939,0.00002411754,0.0001217186,0.0002373309,0.0001598576,0.002717304],"genre_scores_gemma":[0.9809018,0.00005779074,0.01795308,0.00002268284,0.000002929557,0.00006056603,0.000158554,0.00003064464,0.0008120239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003212593,"threshold_uncertainty_score":0.00638783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2375354828860457,"score_gpt":0.4265680839835174,"score_spread":0.1890326010974717,"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."}}