{"id":"W1500434646","doi":"10.1109/icip.2004.1421731","title":"Estimation of mixtures of probabilistic pca with stochastic em for the 3d biplanar reconstruction of scoliotic rib cage","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université de Montréal","funders":"","keywords":"Probabilistic logic; Principal component analysis; Expectation–maximization algorithm; Minification; Maximization; Computer science; Mathematics; Artificial intelligence; Energy minimization; Iterative reconstruction; Pattern recognition (psychology); Mathematical optimization; Algorithm; Statistics; Maximum likelihood","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":[0.001964271,0.0008296078,0.0007851203,0.00097381,0.0003309958,0.0008128575,0.0009090776,0.0009049006,0.0008175545],"category_scores_gemma":[0.005522316,0.0008992403,0.001302152,0.0007761754,0.0007556205,0.001108122,0.001067312,0.001070034,0.0005757756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004877158,"about_ca_system_score_gemma":0.0007594118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002198825,"about_ca_topic_score_gemma":0.00245704,"domain_scores_codex":[0.9991646,0.0003940493,0.00003945496,0.0001453662,0.0002113884,0.00004517813],"domain_scores_gemma":[0.9986343,0.0008577516,0.0001356057,0.0001580063,0.0001758663,0.00003849527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00014602,0.00004347921,0.001324477,0.0000915539,0.0001303784,0.00006301481,0.00008859866,0.8230503,0.009353128,0.01245474,0.001171308,0.152083],"study_design_scores_gemma":[0.000003827885,0.000008238534,0.0002321309,0.000002890393,0.000004991913,0.00002391128,0.000005224469,0.9946204,0.001266463,0.003457534,0.0003644935,0.000009830798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003273875,0.00004047364,0.9963911,0.00002479579,0.000003343134,0.000007096103,0.00001481413,0.0001599903,0.00008449448],"genre_scores_gemma":[0.1688634,0.0002675331,0.8293311,0.00005388475,0.00002902172,0.000132327,0.0003468111,0.0002003475,0.000775526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002198825,"threshold_uncertainty_score":0.0103882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0130000198637166,"score_gpt":0.2642931776818289,"score_spread":0.2512931578181123,"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."}}