{"id":"W2169816047","doi":"10.1109/icpr.2000.903600","title":"Optimal line detector","year":2002,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Detector; Infinite impulse response; Computer science; Line (geometry); Impulse (physics); Algorithm; Gaussian; Finite impulse response; Impulse response; Filter (signal processing); Scale (ratio); Computer vision; Mathematics; Digital filter; Physics; Telecommunications; Mathematical analysis","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":[0.001224796,0.0008059953,0.001846197,0.002789828,0.0008330002,0.001844509,0.001833481,0.002552151,0.01093895],"category_scores_gemma":[0.00340488,0.0007994674,0.0009682605,0.001794778,0.0009494835,0.002639636,0.001510021,0.001033589,0.006964046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008812732,"about_ca_system_score_gemma":0.0016024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078238,"about_ca_topic_score_gemma":0.001185248,"domain_scores_codex":[0.9977903,0.000301611,0.0001023215,0.0005825286,0.0009741852,0.0002490825],"domain_scores_gemma":[0.9982356,0.0003488105,0.0001250042,0.0002932934,0.0009189863,0.00007833999],"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":[0.0003796257,0.000116437,0.0008978506,0.0002180296,0.00006612185,0.0001998014,0.00008030244,0.024243,0.05992691,0.03634951,0.01678872,0.8607337],"study_design_scores_gemma":[0.00008143518,0.0002562883,0.001732748,0.00005473017,0.00008553424,0.002083517,0.00007978601,0.7826059,0.1202369,0.03588989,0.05672868,0.0001646181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001795661,0.0001979279,0.9952483,0.0000541831,0.00004812136,0.00003131857,0.00004789779,0.0008822347,0.001694388],"genre_scores_gemma":[0.06018488,0.0003365038,0.9335095,0.000152432,0.0000709122,0.0001161098,0.0003281368,0.000261991,0.00503954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01093895,"threshold_uncertainty_score":0.03659439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0304056151865112,"score_gpt":0.2767204251535919,"score_spread":0.2463148099670807,"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."}}