{"id":"W4388322906","doi":"10.1093/oso/9780199212903.003.0016","title":"Computational anatomy: Euler–Poincaré image matching","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Toronto","funders":"","keywords":"Diffeomorphism; Matching (statistics); Artificial intelligence; Metric (unit); Computer vision; Computer science; Image (mathematics); Image matching; Euler's formula; Image registration; Mathematics; Pattern recognition (psychology); Pure mathematics; Mathematical analysis; Engineering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007183182,0.0003128985,0.0003615687,0.0002219879,0.00005609242,0.00007263025,0.0001479668,0.0001970724,0.001143368],"category_scores_gemma":[0.000002162052,0.0003168806,0.0002417401,0.00002798038,0.00001817576,0.00007310283,0.00002232468,0.0003498107,0.0006602614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007412126,"about_ca_system_score_gemma":0.0000206296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009407649,"about_ca_topic_score_gemma":0.000007315269,"domain_scores_codex":[0.9990154,0.000003355437,0.000304601,0.0002365081,0.0002547193,0.0001854542],"domain_scores_gemma":[0.9995841,0.00003917495,0.0000376605,0.0001958736,0.00006146618,0.0000816953],"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":[0.000001400492,0.000005885869,6.295901e-7,0.00006690845,0.000308394,0.00005194572,0.00006963937,0.9177625,0.00002057674,0.0353322,0.01127645,0.03510343],"study_design_scores_gemma":[0.0001452475,0.000008934271,0.000005448433,0.0001308888,0.0001301887,0.00001098415,0.000007427025,0.840279,0.00001060297,0.1306784,0.02797213,0.0006207137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00004226612,0.0004719217,0.1940481,0.00009699696,0.00009462657,0.00004203006,0.00002425787,0.0006347777,0.804545],"genre_scores_gemma":[0.1025252,0.0003497044,0.04915392,0.0004299197,0.0006361705,0.000003580843,0.0006058034,0.0002657512,0.8460299],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1448942,"threshold_uncertainty_score":0.9999284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008176097501288376,"score_gpt":0.2164355009869825,"score_spread":0.2082594034856941,"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."}}