{"id":"W2024592371","doi":"10.1016/s0031-3203(99)00155-7","title":"Adaptive morphological operators, fast algorithms and their applications","year":2000,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Algorithm; Image processing; Degrees of freedom (physics and chemistry); Mathematical morphology; Basis (linear algebra); Artificial intelligence; Image (mathematics); Computer vision; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001008573,0.0008820792,0.0008068171,0.00209011,0.000487469,0.001342876,0.0009348575,0.001893904,0.00370215],"category_scores_gemma":[0.003959866,0.0007001578,0.0005089375,0.003742568,0.001231535,0.002356995,0.0008703861,0.001600476,0.001460521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003287882,"about_ca_system_score_gemma":0.0005145712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007286445,"about_ca_topic_score_gemma":0.000632042,"domain_scores_codex":[0.9995303,0.00009716099,0.0000314667,0.00007720191,0.0002369219,0.0000270037],"domain_scores_gemma":[0.9981349,0.001040885,0.000158127,0.0001902855,0.0004292787,0.00004649306],"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":[0.0001582814,0.00005232574,0.0004430425,0.0006067569,0.00005297446,0.0001848144,0.0001887668,0.02805985,0.03268264,0.1674643,0.007141306,0.7629648],"study_design_scores_gemma":[0.0000934228,0.0002219112,0.002277422,0.000223045,0.0001178518,0.001859078,0.0001698367,0.4887199,0.03005527,0.3842754,0.09182729,0.0001595062],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004274771,0.009903952,0.9814447,0.0002960099,0.0002359333,0.00003184145,0.00004548506,0.0003802448,0.003387062],"genre_scores_gemma":[0.06736827,0.01614743,0.9041731,0.0002155882,0.0006120698,0.0001675266,0.0001386719,0.0002076709,0.01096964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00370215,"threshold_uncertainty_score":0.01238495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029368159138252,"score_gpt":0.2651939042146104,"score_spread":0.2349002226232279,"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."}}