{"id":"W3148996144","doi":"10.1109/ccece.2005.1557223","title":"Extraction des contours flous et bruites","year":2006,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec en Outaouais","funders":"","keywords":"Computer science; Smoothing; Extraction (chemistry); Computer vision; Detector; Artificial intelligence; Chromatography","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":[0.001376781,0.001239399,0.001199941,0.004645009,0.001303261,0.001950528,0.000833212,0.003388926,0.00290654],"category_scores_gemma":[0.002798877,0.001188527,0.001003087,0.001987753,0.001285861,0.002257207,0.0004037678,0.001141274,0.003008361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008172527,"about_ca_system_score_gemma":0.0005810559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004292351,"about_ca_topic_score_gemma":0.009259497,"domain_scores_codex":[0.9994634,0.00006847874,0.00005052774,0.0001393303,0.0002203674,0.00005792923],"domain_scores_gemma":[0.9988218,0.0006530254,0.00007186699,0.00006867276,0.0003416835,0.00004288829],"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":[0.0001952448,0.0002267086,0.002434794,0.0008067998,0.0000756413,0.0007069198,0.0007033751,0.05164304,0.0591491,0.1121112,0.02891184,0.7430353],"study_design_scores_gemma":[0.00003516338,0.0003803822,0.006387514,0.0003551329,0.0001410062,0.003339934,0.0005527386,0.4193103,0.1535161,0.09397223,0.3217996,0.0002098624],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005311327,0.004746776,0.9805387,0.001353576,0.0008768631,0.0001120736,0.0001149398,0.001177307,0.005768454],"genre_scores_gemma":[0.0496036,0.02343846,0.855746,0.001390999,0.001411915,0.0001164134,0.0006006331,0.0007151302,0.06697687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004645009,"threshold_uncertainty_score":0.009723306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0145337642371851,"score_gpt":0.3131200450508855,"score_spread":0.2985862808137004,"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."}}