{"id":"W2119879121","doi":"10.1109/tpami.2007.1157","title":"Localization of Shapes Using Statistical Models and Stochastic Optimization","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Concordia University","keywords":"Computer science; Artificial intelligence; Stochastic optimization; Pattern recognition (psychology); Mathematical optimization; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002535152,0.0001153651,0.000186615,0.000525401,0.0001217693,0.00005707254,0.0001108336,0.00004872698,0.00002691432],"category_scores_gemma":[0.000004286231,0.000107003,0.00005474736,0.0006988374,0.00006587633,0.0002769222,0.000004031097,0.00009591969,4.33569e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002087491,"about_ca_system_score_gemma":0.00001008994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007380155,"about_ca_topic_score_gemma":0.0002353343,"domain_scores_codex":[0.9990826,0.00003664678,0.0003117814,0.0002715203,0.0001719316,0.0001254946],"domain_scores_gemma":[0.9994966,0.000106566,0.00008889075,0.0001464447,0.00009656748,0.00006488829],"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":[0.000006050721,0.0000333705,0.0000118188,0.000008120211,0.00005222129,0.000001374459,0.0001286273,0.6487541,0.0001321383,0.00008055256,1.641565e-7,0.3507915],"study_design_scores_gemma":[0.00003150666,0.00006776155,0.00002463533,0.00001157066,0.0001379468,0.000007531558,0.00002356693,0.8468732,0.1521367,0.0005955487,4.00117e-7,0.00008974098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003664225,0.00005055335,0.9993678,0.00001436625,0.00003426266,0.00008182251,0.00001282228,0.00005705639,0.00001488299],"genre_scores_gemma":[0.9590593,0.0000910063,0.04074119,0.00008670684,0.0000051972,0.000002380749,0.000001740153,0.000005804261,0.000006665974],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9586929,"threshold_uncertainty_score":0.4363455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316406237670462,"score_gpt":0.287381107334764,"score_spread":0.2642170449580594,"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."}}