{"id":"W2267267416","doi":"10.1109/cvpr.1998.698644","title":"From parametric warping to the cooperation of local features and global models","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Cluster analysis; Image warping; Computer science; Parametric statistics; A priori and a posteriori; Artificial intelligence; Classification of discontinuities; Dynamic time warping; Partition (number theory); Curvature; Parametric model; Pattern recognition (psychology); Theoretical computer science; Algorithm; Mathematics","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":[0.00006627916,0.00004552664,0.00005687765,0.00003921949,0.00005543645,0.00008461329,0.0001955297,0.00002704598,0.000009804044],"category_scores_gemma":[0.00001405212,0.00002908903,0.00001466088,0.0004551811,0.00001731038,0.0002465672,0.00008378778,0.00003719319,0.000006516071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001587518,"about_ca_system_score_gemma":0.000004047817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006451459,"about_ca_topic_score_gemma":0.00004929697,"domain_scores_codex":[0.9995973,0.00002343816,0.00007959349,0.0001308092,0.00009909959,0.00006979913],"domain_scores_gemma":[0.9996951,0.00003057686,0.00001686775,0.0001864907,0.00004649749,0.00002448311],"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":[0.000003117864,0.0000234055,0.00001309659,0.000002362319,0.000008163829,0.000001739962,0.0005230376,0.002797657,0.0002754025,0.01238407,0.01313446,0.9708335],"study_design_scores_gemma":[0.000103963,0.0001182329,0.0004722373,0.000008436592,0.000003768475,0.00001495682,0.00007752585,0.8228803,0.1681022,0.007447351,0.000665225,0.0001057618],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00556537,0.000262165,0.9906784,0.0008406972,0.00004795512,0.00008166664,0.000001301811,0.00009579874,0.002426701],"genre_scores_gemma":[0.958619,0.00002136456,0.04053999,0.000685483,0.00002256919,0.000004384563,1.712478e-7,0.000001208991,0.0001058069],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9707277,"threshold_uncertainty_score":0.1186216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0159460152347566,"score_gpt":0.2340038809016448,"score_spread":0.2180578656668882,"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."}}