{"id":"W3186931172","doi":"10.1016/j.compbiomed.2021.104681","title":"Automatic bone maturity grading from EOS radiographs in Adolescent Idiopathic Scoliosis","year":2021,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; École de Technologie Supérieure","funders":"Core Research for Evolutional Science and Technology","keywords":"Radiography; Medicine; Convolutional neural network; Pelvis; Scoliosis; Bone age; Orthodontics; Grading (engineering); Artificial intelligence; Radiology; Computer science; Surgery; Anatomy","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":[0.0002943493,0.0001203624,0.0004338617,0.0002690851,0.00002420192,0.000005419742,0.00007452673,0.0001050671,0.00001854554],"category_scores_gemma":[0.00008284475,0.0001017519,0.0000331697,0.0004500724,0.0001564909,0.00002403618,0.0000350364,0.0003190444,0.000001604483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002915205,"about_ca_system_score_gemma":0.00001001702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008505608,"about_ca_topic_score_gemma":0.0000313247,"domain_scores_codex":[0.9991186,0.0001025975,0.0002969934,0.0002135431,0.00005939263,0.0002089019],"domain_scores_gemma":[0.9996595,0.00007057317,0.00002267311,0.0001386892,0.00001044451,0.00009810644],"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":[0.00000789872,0.000140585,0.7856053,0.0007618152,0.0001797895,0.0008976358,0.002042998,0.0002688133,0.01174721,0.0006211443,0.001904971,0.1958218],"study_design_scores_gemma":[0.003055074,0.00005157012,0.4107667,0.008601386,0.0001060486,0.00008130883,0.0003428295,0.5677303,0.0007228465,0.007635034,0.0005148957,0.0003920568],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9465452,0.04241765,0.008660567,0.001456227,0.0007093364,0.00005199962,0.000001469104,0.00009431854,0.00006319755],"genre_scores_gemma":[0.9955446,0.002507441,0.001155174,0.0006161971,0.0001483071,0.000004707205,0.00001550293,0.000006838536,0.000001272158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5674615,"threshold_uncertainty_score":0.4149322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01252412560620727,"score_gpt":0.265907913670849,"score_spread":0.2533837880646418,"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."}}