{"id":"W2142568117","doi":"10.1109/ccece.2007.299","title":"Wavelet-Based Independent Component Analysis For Statistical Shape Modeling","year":2007,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Wavelet; Independent component analysis; Wavelet transform; Artificial intelligence; Computer science; Pattern recognition (psychology); Component (thermodynamics); Statistical model; Component analysis; Range (aeronautics); Principal component analysis; Computer vision; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001297022,0.001353756,0.001123507,0.00142531,0.0004160427,0.000977783,0.001461862,0.00141291,0.003607452],"category_scores_gemma":[0.004919193,0.0005331435,0.001214329,0.00362596,0.0009459564,0.001389858,0.0009809836,0.002414038,0.003684927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006120636,"about_ca_system_score_gemma":0.0009613989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002957371,"about_ca_topic_score_gemma":0.002271423,"domain_scores_codex":[0.999063,0.0002742231,0.00004948054,0.0001657701,0.0004081982,0.00003952593],"domain_scores_gemma":[0.9989005,0.0005261724,0.00009616835,0.0002383049,0.0002141354,0.00002471202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009209642,0.0000705006,0.0004656982,0.0003971563,0.0001800629,0.0002373614,0.000132757,0.297186,0.0199932,0.168048,0.01232388,0.5008734],"study_design_scores_gemma":[0.000007827201,0.00002329219,0.0002423289,0.00002678558,0.00001874526,0.00008255366,0.00001074854,0.9458933,0.002265675,0.03965361,0.01174473,0.00003032225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003917499,0.0004013315,0.9983411,0.0000659892,0.00004123434,0.00001571341,0.00006290773,0.0002415659,0.0004384351],"genre_scores_gemma":[0.05171496,0.003218967,0.940047,0.0001412842,0.0002280986,0.0003324449,0.0008014177,0.0002942998,0.003221496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003607452,"threshold_uncertainty_score":0.01206815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03986839779239713,"score_gpt":0.3153979374935574,"score_spread":0.2755295397011603,"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."}}