{"id":"W2103856694","doi":"10.1109/iembs.2007.4352426","title":"2D/3D Registration of Multiple Bones","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Kingston General Hospital","funders":"","keywords":"Computer vision; Artificial intelligence; Image registration; Radiography; Wrist; Computer science; Object (grammar); Carpal bones; Matching (statistics); Image (mathematics); Medicine; Anatomy; Radiology","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":[0.0002377773,0.00007324525,0.0001227896,0.00006938358,0.00002046922,0.00002232309,0.00008942094,0.00004597491,0.00005477175],"category_scores_gemma":[0.0001694256,0.00006843958,0.00002944823,0.0001581803,0.00005201013,0.0001085957,0.000009165651,0.00009071108,0.00001092242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001105738,"about_ca_system_score_gemma":0.000009463943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002037638,"about_ca_topic_score_gemma":0.000004992086,"domain_scores_codex":[0.9993986,7.566633e-7,0.0002065552,0.00009479369,0.0001516718,0.0001476239],"domain_scores_gemma":[0.9996841,0.00002396931,0.00004134114,0.00004812922,0.0001340259,0.00006842685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001542566,0.00008315577,0.1391032,0.0009761881,0.0001184291,0.000007291241,0.004725929,0.0001017233,0.6662288,0.008543768,0.00945954,0.1706366],"study_design_scores_gemma":[0.0008597558,0.00006226539,0.02794339,0.0004930152,0.0001294435,0.00001598839,0.003112382,0.5665991,0.3793556,0.002204698,0.01854883,0.000675536],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8968421,0.0001160309,0.06024522,0.0001256918,0.00009395011,0.00005375397,0.000001425162,0.0002213893,0.04230047],"genre_scores_gemma":[0.9973708,0.00003230778,0.002201885,0.00001720619,0.00005829307,0.000002355901,0.00000301063,0.000007707953,0.0003063942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5664974,"threshold_uncertainty_score":0.2790885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063440627836565,"score_gpt":0.2400542496406699,"score_spread":0.2194198433623042,"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."}}