{"id":"W4411962717","doi":"10.1016/j.ostima.2025.100322","title":"FINITE ELEMENT MODELING OF IN VIVO HUMAN KNEE BONES USING HR-PQCT: EFFECTS OF BOUNDARY CONDITIONS AND MODEL CONFIGURATION ON PREDICTED STRAIN ENERGY DENSITY","year":2025,"lang":"en","type":"article","venue":"Osteoarthritis Imaging","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Bone and Joint Health Institute; University of Calgary","funders":"","keywords":"Finite element method; In vivo; Strain (injury); Strain energy; Boundary (topology); Materials science; Boundary value problem; Mechanics; Structural engineering; Physics; Medicine; Mathematics; Anatomy; Mathematical analysis; Engineering; Biology","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":[0.0004949537,0.0005680554,0.0004046348,0.0004083792,0.0002031264,0.0006559995,0.0007462896,0.001058302,0.00239486],"category_scores_gemma":[0.001493463,0.0004157654,0.0004471724,0.0002650647,0.0004535022,0.0002871192,0.0003727418,0.0002970149,0.0005102467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002869854,"about_ca_system_score_gemma":0.0005231712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004649457,"about_ca_topic_score_gemma":0.003846388,"domain_scores_codex":[0.9997734,0.00005333014,0.00002459132,0.00004522459,0.00008412482,0.00001937048],"domain_scores_gemma":[0.9994919,0.0002910286,0.0000770822,0.00004606271,0.00007371835,0.00002007381],"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":[0.0001735733,0.000156104,0.005364995,0.0001828173,0.00002654243,0.0002260931,0.000202883,0.932412,0.04608164,0.0004840954,0.0002118446,0.01447732],"study_design_scores_gemma":[0.00001790885,0.0001273458,0.003688,0.00002967994,0.0000136624,0.0001658471,0.00004501708,0.9817775,0.01351546,0.0001622976,0.0004389938,0.00001817464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7529898,0.0004024867,0.2415568,0.0001326153,0.00003414642,0.0001884052,0.0008780958,0.0008241748,0.002993531],"genre_scores_gemma":[0.9632862,0.0001432087,0.0350097,0.00002919843,0.000004116239,0.000113127,0.0003188719,0.0000769073,0.00101873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004649457,"threshold_uncertainty_score":0.0092448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006887584020269571,"score_gpt":0.2214210208390368,"score_spread":0.2145334368187673,"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."}}