{"id":"W4254927362","doi":"10.1109/ccv.1988.590036","title":"Organization Of Smooth Image Curves At Multiple Scales","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Image (mathematics); Computer science; Computer vision; Artificial intelligence","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":[0.0004531047,0.0005586128,0.0004527844,0.003131284,0.0005471097,0.002096701,0.00062615,0.0007843908,0.003297073],"category_scores_gemma":[0.00298617,0.0006366088,0.0003675797,0.001805558,0.0008896362,0.001624154,0.0009300869,0.0007586259,0.0008647825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005863517,"about_ca_system_score_gemma":0.0005726129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001273948,"about_ca_topic_score_gemma":0.001172857,"domain_scores_codex":[0.9997682,0.00002800438,0.00001117721,0.00005366746,0.00009448017,0.00004439791],"domain_scores_gemma":[0.9983945,0.0003648636,0.0002703014,0.0002851124,0.0005146147,0.0001705435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005299565,0.0002194568,0.008074996,0.0004497108,0.00009099014,0.0009695526,0.001685768,0.1347078,0.3291739,0.1054436,0.003791645,0.4148626],"study_design_scores_gemma":[0.00003976578,0.0002554575,0.02223239,0.00007491208,0.00006399057,0.0006566779,0.0004527658,0.8168099,0.05680002,0.09325211,0.009262254,0.00009991722],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2645609,0.0006185911,0.7264667,0.0003605022,0.00004811777,0.000129609,0.000223441,0.001091167,0.006500959],"genre_scores_gemma":[0.7591169,0.00101093,0.2310409,0.0000642566,0.00008169556,0.00007624397,0.0003778047,0.0008253296,0.007406018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003297073,"threshold_uncertainty_score":0.01102978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009354881054286363,"score_gpt":0.2583366177279509,"score_spread":0.2489817366736645,"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."}}