{"id":"W2990371092","doi":"10.48550/arxiv.1911.10352","title":"Shape Detection of Liver From 2D Ultrasound Images","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Ultrasound; Speckle noise; Computer science; Artificial intelligence; Computer vision; Ultrasound imaging; Noise (video); Radiology; Speckle pattern; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005039328,0.0006049717,0.0004764834,0.002407136,0.0002068832,0.001117796,0.0005058067,0.001073376,0.001025667],"category_scores_gemma":[0.002063948,0.0004262119,0.000641757,0.00109373,0.0003502698,0.000474766,0.0005977516,0.0003230809,0.001077316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002590718,"about_ca_system_score_gemma":0.0003126373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001442681,"about_ca_topic_score_gemma":0.001772401,"domain_scores_codex":[0.9993966,0.0001017858,0.0000397804,0.0001157345,0.0002831381,0.0000628706],"domain_scores_gemma":[0.9992105,0.0002462451,0.0001259877,0.0001422789,0.000229045,0.0000459289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007664716,0.0001032259,0.00976468,0.0003379234,0.0001148577,0.0006929453,0.0003026972,0.04077283,0.474389,0.001135331,0.002004714,0.4696155],"study_design_scores_gemma":[0.00002867731,0.0002667899,0.03126235,0.00004189925,0.00006253076,0.003120292,0.0001863172,0.6937677,0.2655925,0.001353761,0.004234931,0.00008230432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.268956,0.001328057,0.7231805,0.0003362099,0.0001374982,0.0001225956,0.0004752282,0.003247287,0.0022166],"genre_scores_gemma":[0.6329779,0.001226852,0.3607194,0.0001823951,0.0001039979,0.00006315945,0.001349909,0.0003856516,0.002990793],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002407136,"threshold_uncertainty_score":0.003431201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04859764133889784,"score_gpt":0.1967864485548839,"score_spread":0.1481888072159861,"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."}}