{"id":"W2144645463","doi":"10.1109/tip.2011.2175738","title":"JUDOCA: JUnction Detection Operator Based on Circumferential Anchors","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Edge detection; Image gradient; Enhanced Data Rates for GSM Evolution; Computer vision; Operator (biology); Detector; Gaussian; Artificial intelligence; Obstacle; Directional derivative; Computer science; Mathematics; Algorithm; Image processing; Image (mathematics); Geometry; Optics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008068436,0.0002251614,0.0001481511,0.000291205,0.00030536,0.0001112243,0.0000776553,0.000127472,0.000164782],"category_scores_gemma":[0.000004176854,0.0002360317,0.00008189114,0.0003854959,0.00003994964,0.0003648963,2.825688e-7,0.0002901843,0.00007316328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001331422,"about_ca_system_score_gemma":0.00003535406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002352283,"about_ca_topic_score_gemma":0.00002855864,"domain_scores_codex":[0.9989831,0.00003250213,0.0002520308,0.000268289,0.0002138578,0.000250208],"domain_scores_gemma":[0.9995603,0.00001503972,0.00003631972,0.0001902786,0.0001060736,0.0000919888],"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":[0.0001077564,0.0002024277,0.000006572855,0.0001569969,0.00002237392,0.000006293644,0.0002761685,0.7520822,0.08244712,0.000003493618,0.00003396548,0.1646547],"study_design_scores_gemma":[0.0003487801,0.0000948723,0.00007311276,0.0000664446,0.00003732177,0.000002793262,0.00003634493,0.6193211,0.3797635,0.00001584984,0.00004887982,0.000190933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01876469,0.00002068818,0.9777188,0.00001289442,0.001137469,0.0001680348,0.000006661944,0.0005555038,0.001615281],"genre_scores_gemma":[0.9962379,0.00001358899,0.003417918,0.00008440222,0.00008783366,0.00003948693,0.000005584558,0.00007201644,0.00004128924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9774732,"threshold_uncertainty_score":0.9625092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01664171034390982,"score_gpt":0.2057188105421309,"score_spread":0.189077100198221,"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."}}