{"id":"W2028532540","doi":"10.2200/s00301ed1v01y201010bme038","title":"Analysis of Oriented Texture with Applications to the Detection of Architectural Distortion in Mammograms","year":2010,"lang":"en","type":"article","venue":"Synthesis lectures on biomedical engineering","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Orientation (vector space); Artificial intelligence; Computer vision; Field (mathematics); Context (archaeology); Distortion (music); Pattern recognition (psychology); Geography; Mathematics; Geometry","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":[0.0002778234,0.0001064272,0.0002015337,0.0006994997,0.00002682843,0.00001323639,0.0004249964,0.00007279019,0.00001353415],"category_scores_gemma":[0.0003884886,0.00006519107,0.00006796417,0.002709626,0.00008350927,0.00004156848,0.00004242018,0.0002582413,8.446971e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002869101,"about_ca_system_score_gemma":0.00001841844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005991904,"about_ca_topic_score_gemma":0.0001756637,"domain_scores_codex":[0.9988914,0.00003157897,0.000269158,0.0002238321,0.0004341102,0.0001499491],"domain_scores_gemma":[0.9990387,0.0003274227,0.00008394043,0.0004084634,0.00004451002,0.00009694142],"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":[0.00001852357,0.00009352627,0.0001591895,0.00002882474,0.000109508,0.000001299772,0.0003451692,0.004128691,0.2867992,0.0003579348,0.000004465384,0.7079537],"study_design_scores_gemma":[0.0001933096,0.0002828079,0.04700036,0.00009617548,0.000149698,0.00000855775,0.00002690478,0.1282885,0.8220041,0.00004707697,0.001640278,0.0002622159],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04656983,0.00001302468,0.9526155,0.0004013585,0.00005508462,0.0002467352,0.000005242211,0.000083206,0.000009995954],"genre_scores_gemma":[0.9637659,0.00000138676,0.03595945,0.00005980493,0.00002534065,0.0001754595,0.000004421852,0.000006492682,0.000001744126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.917196,"threshold_uncertainty_score":0.2658415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003744429129450684,"score_gpt":0.2275093588773772,"score_spread":0.2237649297479265,"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."}}