{"id":"W2109825458","doi":"10.1109/pacrim.2001.953726","title":"Automatic outlier detection in multibeam data using median filtering","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Outlier; Anomaly detection; Computer science; Pattern recognition (psychology); Artificial intelligence; Field (mathematics); Median filter; Data mining; Mathematics; Image processing; Image (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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002915475,0.00009744392,0.0001755439,0.00006664723,0.00004272979,0.00001761504,0.0001554799,0.00004916338,0.0005666014],"category_scores_gemma":[0.001261205,0.00008388445,0.00001478938,0.0001042192,0.00002216457,0.0002142981,0.0001170416,0.0001101401,0.00001672594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004406598,"about_ca_system_score_gemma":0.000003344579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000038787,"about_ca_topic_score_gemma":0.0002018698,"domain_scores_codex":[0.9991084,0.00006155259,0.0002732203,0.0002298728,0.0001229884,0.0002039838],"domain_scores_gemma":[0.9989029,0.0005196284,0.00004973329,0.0004518747,0.00001442221,0.00006149996],"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":[0.000003281748,0.0001451162,0.00003110597,0.0001480754,0.00001366304,0.00002501031,0.0006953441,0.0001915531,0.008973264,0.004127794,0.00009263527,0.9855531],"study_design_scores_gemma":[0.0002130436,0.00001106838,0.00002776832,0.00003691465,0.00001035762,0.000007210411,0.00007194042,0.9246798,0.000966996,0.07378023,0.00008857171,0.0001060567],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0394067,0.00001200189,0.9592003,0.00003172876,0.0001047188,0.0001493548,0.00001284665,0.00008686569,0.0009954718],"genre_scores_gemma":[0.2868353,0.000003560418,0.7129544,0.00002653357,0.00002793945,0.000004006551,0.00000133463,0.00001514421,0.0001317571],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9854471,"threshold_uncertainty_score":0.6203888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4709745651383841,"score_gpt":0.4749747293360978,"score_spread":0.004000164197713707,"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."}}