{"id":"W2488650849","doi":"10.1080/21681163.2016.1216805","title":"Comparison of anatomical parameters of cam femoroacetabular impingement to evaluate hip joint models segmented from CT data","year":2016,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","topic":"Hip disorders and treatments","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Femoroacetabular impingement; Femoral head; Medicine; Acetabulum; Femoral neck; Femur; Nuclear medicine; Segmentation; Orthodontics; Anatomy; Radiology; Artificial intelligence; Computer science; Surgery; Osteoporosis","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":[0.00388584,0.0007599936,0.0005651375,0.002421703,0.00021164,0.001210425,0.0004818556,0.000609709,0.001158598],"category_scores_gemma":[0.01085856,0.0005328783,0.000570266,0.000951261,0.0005279057,0.0005675631,0.0006129263,0.000342553,0.0003401975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002916636,"about_ca_system_score_gemma":0.0003014665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00144711,"about_ca_topic_score_gemma":0.002604286,"domain_scores_codex":[0.9980043,0.0006187232,0.0003394212,0.0004126104,0.0005482028,0.00007673264],"domain_scores_gemma":[0.9955385,0.002126543,0.000659325,0.0008462503,0.0007166167,0.0001126839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003709436,0.0003239088,0.426003,0.0008259358,0.001050605,0.0006326639,0.005873934,0.06162993,0.2823023,0.001305028,0.0008935372,0.2154496],"study_design_scores_gemma":[0.00008677208,0.000824825,0.7466254,0.0001453095,0.0003804121,0.002402881,0.001127302,0.1895058,0.05502726,0.0009619181,0.002734007,0.0001779588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9173829,0.0005128599,0.0801257,0.00003248447,0.00002828799,0.0001524078,0.0004679556,0.0004152759,0.0008820323],"genre_scores_gemma":[0.9639912,0.0001720574,0.03471006,0.00002216205,0.000008992289,0.0001529426,0.0005399752,0.0001597956,0.0002427884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00388584,"threshold_uncertainty_score":0.02055049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09462105142379472,"score_gpt":0.4239685590503353,"score_spread":0.3293475076265405,"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."}}