{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006559201,0.0003228037,0.0003577622,0.002806788,0.0001741904,0.0008296631,0.0003892406,0.0005411039,0.001159098],"category_scores_gemma":[0.001828554,0.0002163719,0.0003192222,0.0005770716,0.0001522235,0.0003442895,0.0003865954,0.0003057437,0.0003829503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001585783,"about_ca_system_score_gemma":0.0002813691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002509851,"about_ca_topic_score_gemma":0.005032104,"domain_scores_codex":[0.9996345,0.00006526791,0.00004706652,0.00007249159,0.0001360116,0.00004465736],"domain_scores_gemma":[0.9991371,0.0002502381,0.0001300783,0.0000471562,0.0003596639,0.00007576578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001387406,0.0002118967,0.2453318,0.000441352,0.0001489342,0.000657892,0.000238436,0.008015816,0.1284118,0.0006171771,0.001899801,0.6126378],"study_design_scores_gemma":[0.00007486726,0.0004782513,0.7200252,0.0001481474,0.0002067626,0.004230963,0.0004672896,0.228634,0.04133662,0.0007661714,0.003563217,0.00006851852],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9426311,0.002202518,0.05145077,0.0001286663,0.00006287533,0.00009088201,0.0008163258,0.0008814196,0.001735431],"genre_scores_gemma":[0.9747882,0.0004862157,0.02292493,0.00002276583,0.00003280287,0.00001823588,0.000707037,0.0000677365,0.0009520699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002806788,"threshold_uncertainty_score":0.004990458,"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."}}