{"id":"W2050208812","doi":"10.1016/j.compbiomed.2013.07.032","title":"Prediction of stress shielding around an orthopedic screw: Using stress and strain energy density as mechanical stimuli","year":2013,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Orthopaedic implants and arthroplasty","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Amirkabir University of Technology; University of Ottawa","keywords":"Stress shielding; Strain energy density function; Stress (linguistics); Context (archaeology); Materials science; Modulus; Finite element method; Electromagnetic shielding; Stress–strain curve; Strain (injury); Bone density; Parametric statistics; Biomechanics; sed; Composite material; Structural engineering; Implant; Deformation (meteorology); Medicine; Osteoporosis; Surgery; Mathematics; Anatomy; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002556364,0.0001675491,0.0004570347,0.0001758351,0.00008351138,0.000006039606,0.00004958415,0.0001991426,0.00005426224],"category_scores_gemma":[0.00007681146,0.0001230834,0.00002099873,0.00009748626,0.0005150805,0.0001030399,0.00008132691,0.0002093502,3.17121e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001654768,"about_ca_system_score_gemma":0.00004200595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008248648,"about_ca_topic_score_gemma":0.0001036909,"domain_scores_codex":[0.9988332,0.0001086472,0.0003607124,0.0003416608,0.0001100936,0.0002456916],"domain_scores_gemma":[0.9992937,0.0001611355,0.0001036519,0.0001574673,0.00005836036,0.0002256473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000228056,0.000253229,0.7902611,0.0002305752,0.0001185258,0.0001241573,0.0006172489,0.00002303722,0.01521893,0.009865439,0.00007978679,0.1829799],"study_design_scores_gemma":[0.0121474,0.007292042,0.8766009,0.003532178,0.0003407548,0.001900149,0.002897248,0.08695716,0.001137108,0.006266777,0.0004387904,0.0004895545],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857169,0.0005581169,0.01255726,0.0003592151,0.0004682091,0.0001938801,0.00003226229,0.00002559057,0.00008857832],"genre_scores_gemma":[0.9967185,0.0005671671,0.001637148,0.0005407333,0.0004060917,0.000003171783,0.0001055264,0.000009425226,0.0000121967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1824904,"threshold_uncertainty_score":0.5019197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03800216107958028,"score_gpt":0.3093181119268033,"score_spread":0.271315950847223,"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."}}