{"id":"W2270427312","doi":"10.5623/cig2011-026","title":"Image Matching and Surface Registration for 3D Reconstruction of a Scoliotic Torso","year":2011,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Scoliosis diagnosis and treatment","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Torso; Photogrammetry; Artificial intelligence; Computer vision; Image registration; Computer science; Scoliosis; 3D reconstruction; Matching (statistics); Surface reconstruction; Surface (topology); Medicine; Mathematics; Image (mathematics); Anatomy; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001140886,0.00006429556,0.0001660114,0.00003399,0.00003503939,0.000008627769,0.00001597369,0.00003484328,0.00006619195],"category_scores_gemma":[0.00005434415,0.00005296036,0.00003641497,0.00004849006,0.00004234591,0.00007363316,0.000007231692,0.00002284076,0.000004529296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002087313,"about_ca_system_score_gemma":0.00002429549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001008093,"about_ca_topic_score_gemma":0.00001467314,"domain_scores_codex":[0.9995304,0.0000111197,0.0001904184,0.0001088255,0.00006991545,0.0000892649],"domain_scores_gemma":[0.9996324,0.00004906924,0.00009183869,0.0001263176,0.00005458934,0.00004574439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00224365,0.005390493,0.631933,0.01115545,0.001992995,0.00008732938,0.02743075,0.00001079604,0.1218388,0.04261774,0.003151549,0.1521475],"study_design_scores_gemma":[0.006917568,0.00275681,0.8615192,0.002792354,0.001404408,0.0005592984,0.002563854,0.003796658,0.09415604,0.02297868,0.0001382644,0.0004169166],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946004,0.0001188555,0.00120595,0.000167974,0.00005830394,0.0005115965,0.000004946662,0.00001942836,0.003312608],"genre_scores_gemma":[0.8678353,0.00003020476,0.1320236,0.00002576959,0.00001923312,0.00002289825,0.000003616153,0.000006855978,0.00003240932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2295862,"threshold_uncertainty_score":0.2159661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03664735018231494,"score_gpt":0.276661086519184,"score_spread":0.240013736336869,"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."}}